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Dr. Vivekananth.P. "The Role of Social Media Forensics in Digital Forensics." International Journal of Engineering and Management Research 12, no. 4 (August 1, 2022): 1–3. http://dx.doi.org/10.31033/ijemr.12.4.1.
Повний текст джерелаАнотація:
Social media forensics collects evidence from social media sites such as Facebook, WhatsApp, TikTok, and Snapchat to identify criminals. This paper discusses social media crimes such as hacking, photo morphing, shopping scams, cyberbullying, and link baiting. The paper deliberates the social media forensics techniques such as evidence collection, storing, analyzing, and preserving; the paper discusses the process of forensics examination in social media forensics. The paper examines the social media forensics tools such as WebPreserver, make a Website Hub, Pipl Search, TinEye, and TweetBeaver and discusses the applications of each device. The paper concludes by discussing the future of social media forensics.
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Bintang, Rauhulloh Ayatulloh, Rusydi Umar, and Anton Yudhana. "Analisis Media Sosial Facebook Lite dengan tools Forensik menggunakan Metode NIST." Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) 21, no. 2 (November 17, 2020): 125. http://dx.doi.org/10.30595/techno.v21i2.8494.
Повний текст джерелаАнотація:
Social Media is becoming very popular among the public today, and the increasing number of social media use has of course a good or bad impact on the course of human life, for example the bad impact is doing cyberbully or chating on social media. Digital forensics is one of the sciences for how to catch criminals in digital which will be needed in evidence in court. Social media criminals need Smartphones to commit digital cybercrime. This research will raise evidence of digital crimes on the Facebook Lite application using forensics. In this study, the forensic tool that will be used is the MOBILEedit Forensic Pro forensic tools with the help of using methods NIST National Institute Of Standars Techlogogy. NIST has a good workflow for extracting digital forensic data. The research results will be obtained in the form of accounts Id, audio, conversations, and images
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Rocha, Anderson, Walter J. Scheirer, Christopher W. Forstall, Thiago Cavalcante, Antonio Theophilo, Bingyu Shen, Ariadne R. B. Carvalho, and Efstathios Stamatatos. "Authorship Attribution for Social Media Forensics." IEEE Transactions on Information Forensics and Security 12, no. 1 (January 2017): 5–33. http://dx.doi.org/10.1109/tifs.2016.2603960.
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Ashraf, Noorulain, Danish Mahmood, Muath A. Obaidat, Ghufran Ahmed, and Adnan Akhunzada. "Criminal Behavior Identification Using Social Media Forensics." Electronics 11, no. 19 (October 1, 2022): 3162. http://dx.doi.org/10.3390/electronics11193162.
Повний текст джерелаАнотація:
Human needs consist of five levels, which are: physiological needs, safety needs, love needs, esteem needs and self-actualization. All these needs lead to human behavior. If the environment of a person is positive, healthy behavior is developed. However, if the environment of the person is not healthy, it can be reflected in his/her behavior. Machines are intelligent enough to mimic human intelligence by using machine learning and artificial intelligence techniques. In the modern era, people tend to post their everyday life events on social media in the form of comments, pictures, videos, etc. Therefore, social media is a significant way of knowing certain behaviors of people such as abusive, aggressive, frustrated and offensive behaviors. Behavior detection by crawling the social media profile of a person is a crucial and important idea. The challenge of behavior detection can be sorted out by applying social media forensics on social media profiles, which involves NLP and deep learning techniques. This paper is based on the study of state of the art work on behavior detection, and based on the research, a model is proposed for behavior detection. The proposed model outperformed with an F1 score of 87% in the unigram + bigram class, and in the bigram + trigram class, it gave an F1 score of 88% when compared with models applied on state of the art work. This study is a great benefit to cybercrime and cyber-security agencies in shortlisting the profiles containing certain behaviors to prevent crimes in the future.
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Farid, Hany. "Image Forensics." Annual Review of Vision Science 5, no. 1 (September 15, 2019): 549–73. http://dx.doi.org/10.1146/annurev-vision-091718-014827.
Повний текст джерелаАнотація:
From mainstream media outlets to social media and everything in between, doctored photographs are appearing with growing frequency and sophistication. The resulting lack of trust is impacting law enforcement, national security, the media, e-commerce, and more. While some types of manipulations can be detected with a careful visual examination, our visual system seems unable to reliably detect other types of manipulations. The field of image forensics has emerged to help return some trust in photography. I describe the perceptual limits of detecting manipulated images, as well as representative examples of computational techniques for authenticating images.
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Wafula, George, and Andrew M. "Social Media Forensics for Hate Speech Opinion Mining." International Journal of Computer Applications 155, no. 1 (December 15, 2016): 39–47. http://dx.doi.org/10.5120/ijca2016912258.
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Hariyadi, Dedy, Hendro Wijayanto, and Indah Daila Sari. "PAZIIM DIGITAL EVIDENCE ANALYSIS APPLICATION ON ANDROID SMARTPHONES WITH A LOGICAL ACQUISITION APPROACH." Cyber Security dan Forensik Digital 2, no. 2 (November 28, 2019): 52–56. http://dx.doi.org/10.14421/csecurity.2019.2.2.1603.
Повний текст джерелаАнотація:
The use of social media in Indonesia has increased very rapidly in 2018 compared to the previous year. This makes a lot of social media made by the children of the nation appear, one of which is Paziim. Socializing on the internet is very easy to leak personal data. There are three aspects that can be utilized on online social networks (OSN) in the disclosure of private data to the public, namely the strength of the relationship (strong or weak), the type of relationship and the characteristics of one's habits. Mobile forensics is needed to analyze digital evidence on social media applications installed on Android smartphones. Indonesia through the National Standardization Agency (BSN) also issued standards related to digital forensics. Standards which are derived from ISO / IEC regulate Security Techniques - Guidelines for the Identification, Collection, Acquisition and Preservation of Digital Evidence. This standardization is known as SNI ISO / IEC 27037: 2014. From the results of cell phone forensic analysis on the Paziim application, the results found the username, coordinates, device models, and operators used by users in SQLite Web_Data and OneSignal.xml files
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Zuhriyanto, Ikhsan, Anton Yudhana, and Imam Riadi. "Comparative analysis of Forensic Tools on Twitter applications using the DFRWS method." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 4, no. 5 (October 30, 2020): 829–36. http://dx.doi.org/10.29207/resti.v4i5.2152.
Повний текст джерелаАнотація:
Current crime is increasing, one of which is the crime of using social media, although no crime does not leave digital evidence. Twitter application is a social media that is widely used by its users. Acts of crime such as fraud, insults, hate speech, and other crimes lately use many social media applications, especially Twitter. This research was conducted to find forensic evidence on the social media Twitter application that is accessed using a smartphone application using the Digital Forensics Research Workshop (DFRWS) method. These digital forensic stages include identification, preservation, collection, examination, analysis, and presentation in finding digital evidence of crime using the MOBILedit Forensic Express software and Belkasoft Evidence Center. Digital evidence sought on smartphones can be found using case scenarios and 16 variables that have been created so that digital proof in the form of smartphone specifications, Twitter accounts, application versions, conversations in the way of messages and status. This study's results indicate that MOBILedit Forensic Express digital forensic software is better with an accuracy rate of 85.75% while Belkasoft Evidence Center is 43.75%.
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Anggraini, Fitri, Herman Herman, and Anton Yudhana. "Analisis Forensik Aplikasi TikTok Pada Smartphone Android Menggunakan Framework Association of Chief Police Officers." JURIKOM (Jurnal Riset Komputer) 9, no. 4 (August 30, 2022): 1117. http://dx.doi.org/10.30865/jurikom.v9i4.4738.
Повний текст джерелаАнотація:
TikTok is the most popular social media app that ranks sixth in the world in January 2022 according to We Are Media & Hootsuite. Along with the increasing number of uses of this application, the negative impacts it causes are also increasing, ranging from fraud, cyberbullying, to the spread of fake news (hoax). This study focuses on the negative impact of defamation. The purpose of the research is to plan and implement a digital forensics process using the Association of Chief Police Officers (ACPO) framework to raise evidence of defamation cases on the TikTok application. The forensic process is carried out in the form of static forensics on cases that are intentionally made in the form of simulating TikTok postings using an android smartphone. This research combines the ACPO forensics framework with the Magnet Axiom forensics tools. The combination of the two succeeded in raising 77% of evidence in the form of data messages, videos, and hashtags. Where these data have been previously defined as initial data posted in the simulation process
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Pawitradi, Gede, and I. Ketut Gede Suhartana. "Acquisition of LINE Digital Social Media Evidence Using the National Institute of Justice (NIJ) Method." JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) 8, no. 2 (January 8, 2020): 129. http://dx.doi.org/10.24843/jlk.2019.v08.i02.p04.
Повний текст джерелаАнотація:
Nowadays the use of social media has developed very rapidly over time. With very easy to use and also higher security than ordinary messaging services, making one of the factors of social media is very often used in today's world. But behind it all, social media such as LINE is very vulnerable to become one of the crime facilities, one of which is cyberbullying. To follow up on the cyberbullying activity, a forensic cellphone needs to be carried out to find evidence which is then useful to send to court. This study uses the LINE application as cyberbullying crime media, as well as using the National Institute of Justice (NIJ) method. The National Institute of Justice (NIJ) method has five basic stages namely, preparation, collection, examination, analysis, and reporting. In this study using the MOBILedit Forensic tool, and DB Browser for SQLite. It is hoped that the research carried out can help in solving cyberbullying on social media LINE on mobile forensics
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Shahbazi, Zeinab, and Yung-Cheol Byun. "NLP-Based Digital Forensic Analysis for Online Social Network Based on System Security." International Journal of Environmental Research and Public Health 19, no. 12 (June 8, 2022): 7027. http://dx.doi.org/10.3390/ijerph19127027.
Повний текст джерелаАнотація:
Social media evidence is the new topic in digital forensics. If social media information is correctly explored, there will be significant support for investigating various offenses. Exploring social media information to give the government potential proof of a crime is not an easy task. Digital forensic investigation is based on natural language processing (NLP) techniques and the blockchain framework proposed in this process. The main reason for using NLP in this process is for data collection analysis, representations of every phase, vectorization phase, feature selection, and classifier evaluation. Applying a blockchain technique in this system secures the data information to avoid hacking and any network attack. The system’s potential is demonstrated by using a real-world dataset.
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Alonso-Fernandez, Fernando, Nicole Mariah Sharon Belvisi, Kevin Hernandez-Diaz, Naveed Muhammad, and Josef Bigun. "Writer Identification Using Microblogging Texts for Social Media Forensics." IEEE Transactions on Biometrics, Behavior, and Identity Science 3, no. 3 (July 2021): 405–26. http://dx.doi.org/10.1109/tbiom.2021.3078073.
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Zampoglou, Markos, Symeon Papadopoulos, Yiannis Kompatsiaris, Ruben Bouwmeester, and Jochen Spangenberg. "Web and Social Media Image Forensics for News Professionals." Proceedings of the International AAAI Conference on Web and Social Media 10, no. 2 (August 4, 2021): 159–66. http://dx.doi.org/10.1609/icwsm.v10i2.14845.
Повний текст джерелаАнотація:
User-generated content -commonly referred to as "eyewitness media"- has become an essential component in journalism and news reporting. Increasingly more news providers, such as news agencies, broadcasters and Web-only players have set up teams of dedicated investigators or are in the process of training parts of their journalistic workforce to gather and evaluate material from social networks and the Web. If verified, such content can be invaluable in delivering a news story. However, while source checking and verification is as old as journalism itself, the verification of digital material is a relatively young field, with protocols and assisting tools still being developed. In this work, we present our efforts towards a Web-based image verification platform. The platform, currently in its alpha stage, features image tampering detection using a number of state-of-the-art algorithms and image metadata visualization. We discuss the current strengths and limitations of the platform and the implemented state-of-the-art with respect to the specific requirements of the task, resulting from its Web-based nature and its intended use by news investigators with limited expertise in the domain of image forensics.
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Riadi, Imam, Herman Herman, and Nur Hamida Siregar. "Mobile Forensic of Vaccine Hoaxes on Signal Messenger using DFRWS Framework." MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer 21, no. 3 (July 31, 2022): 489–502. http://dx.doi.org/10.30812/matrik.v21i3.1620.
Повний текст джерелаАнотація:
The COVID-19 pandemic is one of the factors that has increased the use of social media. One of the negative impacts of using social media is the occurrence of cybercrime. The possibility of cybercrime can also happen on one of the social media platforms, such as the Signal Messenger application. In the investigation process, law enforcement needs mobile forensic methods and appropriate forensic tools so that the digital evidence found on the perpetrator's smartphone can be accepted by the court. This research aims to get digital evidence from cases of spreading the COVID-19 vaccine hoaxes. The method used in this research is a mobile forensics method based on the Digital Forensic Research Workshop (DFRWS) framework. The DFRWS framework consists of identification, preservation, collection, examination, analysis, and preservation. The results showed that the MOBILedit tool could reveal digital evidence in the form of application information and contact information with a performance value of 22.22%. Meanwhile, Magnet AXIOM cannot reveal digital evidence at all. The research results were obtained following the expected research objectives.
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Chiang, Chang-Po, Shiuh-Jeng Wang, and Yu-Shu Chen. "Manipulating cyber army in pilot case forensics on social media." Journal of Supercomputing 78, no. 6 (January 4, 2022): 7749–67. http://dx.doi.org/10.1007/s11227-021-04172-x.
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Arshad, Humaira, Saima Abdullah, Moatsum Alawida, Abdulatif Alabdulatif, Oludare Isaac Abiodun, and Omer Riaz. "A Multi-Layer Semantic Approach for Digital Forensics Automation for Online Social Networks." Sensors 22, no. 3 (February 1, 2022): 1115. http://dx.doi.org/10.3390/s22031115.
Повний текст джерелаАнотація:
Currently, law enforcement and legal consultants are heavily utilizing social media platforms to easily access data associated with the preparators of illegitimate events. However, accessing this publicly available information for legal use is technically challenging and legally intricate due to heterogeneous and unstructured data and privacy laws, thus generating massive workloads of cognitively demanding cases for investigators. Therefore, it is critical to develop solutions and tools that can assist investigators in their work and decision making. Automating digital forensics is not exclusively a technical problem; the technical issues are always coupled with privacy and legal matters. Here, we introduce a multi-layer automation approach that addresses the automation issues from collection to evidence analysis in online social network forensics. Finally, we propose a set of analysis operators based on domain correlations. These operators can be embedded in software tools to help the investigators draw realistic conclusions. These operators are implemented using Twitter ontology and tested through a case study. This study describes a proof-of-concept approach for forensic automation on online social networks.
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Riadi, Imam, Anton Yudhana, and Muhamad Caesar Febriansyah Putra. "Forensic Tool Comparison on Instagram Digital Evidence Based on Android with The NIST Method." Scientific Journal of Informatics 5, no. 2 (November 29, 2018): 235–47. http://dx.doi.org/10.15294/sji.v5i2.16545.
Повний текст джерелаАнотація:
The growth of Android-based smartphone users to access media in communicating using Instagram social media is very fast. Activities are carried out when using Instagram social media in communicating to share information such as sending chat texts and pictures. A large number of Instagram users make this application vulnerable to abuse of Instagram such as pornography crimes from Instagram users. This case can be forensic to get digital evidence in the form of chat text and pictures from Instagram messenger is a feature of Instagram. The investigation in this study uses the National Institute of Standards and Technology (NIST) method which provides several stages of collecting, examining, analyzing, reporting while forensic tools use forensic oxygen and axiom magnets. The results of the recovery and comparison of data result using Oxygen forensics and Axiom Magnets obtained digital evidence in the form of data in the form of images and chat. The data obtained by Magnet Axiom is 100% while forensic oxygen is 84%. These data are the results of the performance of both forensic applications in obtaining digital evidence that has been deleted from the Instagram messenger.
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Marcon, Federico, Cecilia Pasquini, and Giulia Boato. "Detection of Manipulated Face Videos over Social Networks: A Large-Scale Study." Journal of Imaging 7, no. 10 (September 28, 2021): 193. http://dx.doi.org/10.3390/jimaging7100193.
Повний текст джерелаАнотація:
The detection of manipulated videos represents a highly relevant problem in multimedia forensics, which has been widely investigated in the last years. However, a common trait of published studies is the fact that the forensic analysis is typically applied on data prior to their potential dissemination over the web. This work addresses the challenging scenario where manipulated videos are first shared through social media platforms and then are subject to the forensic analysis. In this context, a large scale performance evaluation has been carried out involving general purpose deep networks and state-of-the-art manipulated data, and studying different effects. Results confirm that a performance drop is observed in every case when unseen shared data are tested by networks trained on non-shared data; however, fine-tuning operations can mitigate this problem. Also, we show that the output of differently trained networks can carry useful forensic information for the identification of the specific technique used for visual manipulation, both for shared and non-shared data.
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Haggerty, John, Mark C. Casson, Sheryllynne Haggerty, and Mark J. Taylor. "A Framework for the Forensic Analysis of User Interaction with Social Media." International Journal of Digital Crime and Forensics 4, no. 4 (October 2012): 15–30. http://dx.doi.org/10.4018/jdcf.2012100102.
Повний текст джерелаАнотація:
The increasing use of social media, applications or platforms that allow users to interact online, ensures that this environment will provide a useful source of evidence for the forensics examiner. Current tools for the examination of digital evidence find this data problematic as they are not designed for the collection and analysis of online data. Therefore, this paper presents a framework for the forensic analysis of user interaction with social media. In particular, it presents an inter-disciplinary approach for the quantitative analysis of user engagement to identify relational and temporal dimensions of evidence relevant to an investigation. This framework enables the analysis of large data sets from which a (much smaller) group of individuals of interest can be identified. In this way, it may be used to support the identification of individuals who might be ‘instigators’ of a criminal event orchestrated via social media, or a means of potentially identifying those who might be involved in the ‘peaks’ of activity. In order to demonstrate the applicability of the framework, this paper applies it to a case study of actors posting to a social media Web site.
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Imam Riadi, Sunardi, and Panggah Widiandana. "Investigating Cyberbullying on WhatsApp Using Digital Forensics Research Workshop." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 4, no. 4 (August 20, 2020): 730–35. http://dx.doi.org/10.29207/resti.v4i4.2161.
Повний текст джерелаАнотація:
Cyberbullying in group conversations in one of the instant messaging applications is one of the conflicts that occur due to social media, specifically WhatsApp. This study conducted digital forensics to find evidence of cyberbullying by obtaining work in the Digital Forensic Research Workshop (DFRWS). The evidence was investigated using the MOBILedit Forensic Express tool as an application for evidence submission and the Cosine Similarity method to approve the purchase of cyberbullying cases. This research has been able to conduct procurement to reveal digital evidence on the agreement in the Group's features using text using MOBILedit. Identification using the Cosine method. Similarities have supported actions that lead to cyberbullying with different levels Improved Sqrt-Cosine (ISC) value, the largest 0.05 and the lowest 0.02 based on conversations against requests.
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Wijanarko, Anas Aditya, Ridwan Ridwan, and Aliyth Prakarsa. "Peran Digital Forensik dalam Pembuktian Tempus Delicti Sebagai Upaya Pertanggungjawaban Pidana Pelaku Pembuat Video Pornografi." PAMPAS: Journal of Criminal Law 2, no. 2 (October 22, 2021): 68–88. http://dx.doi.org/10.22437/pampas.v2i2.14771.
Повний текст джерелаАнотація:
This article aims to discuss the role of digital forensics in proving tempus delicti as an effort to criminal liability for the makers of pornographic video (case study: vina garut video. The role of digital forensics is used in the recent case of pornographic content, namely the Vina Garut video case. This case is a case of immoral videos showing pornographic scenes between several men and a woman, there are at least two videos of Vina Garut that are spread on social media and this makes the Garut Resort Police immediately move to investigate this case. This type of research is empirical juridical. The result of this study lead to the conclusion that based on the results of digital forensic tests, criminal liability should be imposed on the perpetrator of pornographic videos in this Vina Garut video case, namely against female perpetrators in this case with the initials PA can be categorized as victims while against other perpetrators with initials W and D are subject to Article 37 in conjunction with Article 11 of the Pornography Law, this is because the digital forensic results of the PA can still be categorized as victims. ABSTRAK Penelitian ini bertujuan untuk untuk membahas tentang peran digital forensik dalam pembuktian tempus delicti sebagai upaya pertanggungjawaban pidana pelaku pembuat video pornografi (studi kasus: video vina garut). Peran digital forensic digunakan dalam kasus konten pornografi yang belum lama ini terjadi yaitu kasus video Vina Garut. Kasus ini merupakan kasus video asusila yang memperlihatkan adegan bermuatan pornografi antara beberapa pria dengan seorang wanita, setidaknya terdapat dua video Vina Garut yang tersebar di media sosial dan hal tersebut membuat Kepolisian Resor Garut langsung bergerak menyelidiki kasus ini. Tipe penelitian ini adalah penelitian yuridis empiris. Hasil Penelitian ini menghasilkan kesimpulan bahwa berdasarkan hasil uji digital forensik maka seharusnya pertanggungjawaban pidana yang dikenakan terhadap para pelaku pembuat video pornografi dalam kasus video Vina Garut ini yaitu terhadap pelaku wanita dalam kasus ini dengan inisial PA dapat dikategorikan sebagai korban sedangkan terhadap para pelaku lain dengan inisial W dan D dikenakan Pasal 37 juncto Pasal 11 Undang-Undang Pornografi hal ini dikarenakan berdasarkan hasil digital forensik PA masih dapat dikategorikan sebagai korban.
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Shelke, Priya Makarand, and Rajesh Shardanand Prasad. "Tradeoffs Between Forensics and Anti-Forensics of Digital Images." International Journal of Rough Sets and Data Analysis 4, no. 2 (April 2017): 92–105. http://dx.doi.org/10.4018/ijrsda.2017040107.
Повний текст джерелаАнотація:
Over past few years, we are the spectators of the evolution in the field of information technology, telecommunication and networking. Due to the advancement of smart phones, easy and inexpensive access to the internet and popularity of social networking, capture and use of digital images has increased drastically. Image processing techniques are getting developed at rapidly and at the same time easy to use image tampering soft-wares are also getting readily available. If tampered images are misused, big troubles having deep moral, ethical and lawful allegations may arise. Due to high potential of visual media and the ease in their capture, distribution and storage, we rarely find a field where digital visual data is not used. The value of image as evidence of event must be carefully assessed and it is a call for from different fields of applications. Therefore, in this age of fantasy, image authentication has become an issue of utmost importance.
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Setya, Adi, and Abba Suganda. "Design of Digital Evidence Collection Framework in Social Media Using SNI 27037: 2014." JUITA: Jurnal Informatika 10, no. 1 (May 27, 2022): 127. http://dx.doi.org/10.30595/juita.v10i1.13149.
Повний текст джерелаАнотація:
Social media is a place that people use to socialize. In addition to socializing, social media is also often used as a crime medium by certain people. In the evidentiary process, law enforcers have the duty to present the evidence used by the suspect in committing his crime. The method used in collecting digital evidence from social media must have a clear scientific basis and guidelines. If the method used is not known as a theory or method in digital forensics, this will undermine all expert testimony and evidence presented in the court. Making a framework that can be recognized by all judicial administrators (judges, public prosecutors, attorneys for defendants, witnesses and defendants) is a solution that can be used as a standard so that the evidence process runs well. The framework that has been created by the researcher is an update from the previous framework. The framework design is made using the Composite Logic method. The composite logic method will collaborate with the Digital Forensics Investigation Models framework to produce a new framework. Based on existing data and facts, this research has produced a framework with better performance than the previous framework.
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El-Tayeb, Mahmoud, Ahmed Taha, and Zaki Taha. "Streamed Video Reconstruction for Firefox Browser Forensics." Ingénierie des systèmes d information 26, no. 4 (August 31, 2021): 337–44. http://dx.doi.org/10.18280/isi.260401.
Повний текст джерелаАнотація:
In criminal investigations, the digital evidence extracted from social media may provide exceptional support. Reviewing the history or cache of the web browser may provide a valuable insight into the activity of the suspect. The growing popularity of Internet video streaming creates a risk of this technology misuse. There are a few published research on video reconstruction forensics on the Chrome browser. There is a difference in the methods applied to reconstruct cached video on Chrome from the methods applied to Firefox or any browser. Our primary focus in this research is to examine the forensic procedures required to reconstruct cached video stream data using Twitter and YouTube on the Firefox browser. Some work has been done to reconstruct a cached video on the Chrome browser, but we need more work on the rest of the browsers, most notably the Firefox browser used in this research. Both examination strategies and contemplations displayed are approved and suitable for the forensic study of various streaming platforms as well as the web browser caches.
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Al Jumah, Muhammad Naim, Bambang Sugiantoro, and Yudi Prayudi. "PENERAPAN METODE COMPOSITE LOGIC UNTUK PERANCANGAN FRAMEWORK PENGUMPULAN BUKTI DIGITAL PADA MEDIA SOSIAL." ILKOM Jurnal Ilmiah 11, no. 2 (August 31, 2019): 135–42. http://dx.doi.org/10.33096/ilkom.v11i2.442.135-142.
Повний текст джерелаАнотація:
Social media has become a major part of society. But most of the time social media is used as a way people commit the crime. Due to numerous crimes that use social media, it is essential to design a framework to gather digital evidence on social media. This study develops the design of Framework by implementing Composite Logic Model. A logic Composite model can be used to determine the role model of any variable or pattern that need to collaborate. Composite Logic Model will produce a role model that has a role to produce patterns so that it can produce the same goal. A method of Composite Logic will collaborate with the Digital Forensics Investigation framework to produce a Digital Evidence Collection Framework on Social Media. Based on data and facts, this study has been producing a new framework of gathering digital evidence on social media. The framework has four main stages in the process of collecting digital evidence on social media including pre-process, collection, analysis, and report.
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Nukman, Nukman, Yudi Prayudi, and Fetyata Yudha. "Pengembangan Framework Digital Forensics Investigation (FDFI) Pada Sosial Media Dengan Metode System Development Life Cycle (SDLC)." JATISI (Jurnal Teknik Informatika dan Sistem Informasi) 9, no. 3 (September 13, 2022): 1852–60. http://dx.doi.org/10.35957/jatisi.v9i3.2151.
Повний текст джерелаАнотація:
Dari perkembangan teknologi yang begitu semakin bersaing dan semakin diperlukan dalam kehidupan masyarakat untuk keperluan sehari-harinya di media social seperti yang sering di gunakan oleh masyarakat yaitu Twitter, Facebook, Instagram, Youtube, WhatsApp dan social media lainnya. Tapi di masyarakat umum tidak tahu bahwa data yang di kirim tersebut tersimpan didalam server pusat sehingga orang lain bisa menggunakan data tersebut untuk berbuat kejahatan seperti mengambil indentitas sehingga dapat digunakan sebagai alat untuk berbuat untuk menyebarkan informasi yang tidak falit kejahatan lainnya yang bisa merugikan orang banyak. Maka dari itu peneliti mengembangkan sebuah Framework investigasi di dalam social media sebagai pengumpulan data dengan metode System Development Life Cycle (SDLC). dalam pengembangan framework pengambilan data ini peneliti menggunakan tool Maltego sebagai alat pembuktian identitas pelaku. Framework yang di rancang akan menghasilkan lima tahapan yaitu planning, analysis, design, maintenance, dan implementation. Adapun bukti digital yang akan diperoleh dari tools tersebut diantaranya akun twitter, email addres, phone number, DNS, websaite dan social media.
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El-Tayeb, Mahmoud, Ahmed Taha, and Zaki T. Fayed. "Live-Streamed Video Reconstruction for Web Browser Forensics." Ingénierie des systèmes d information 27, no. 1 (February 28, 2022): 61–66. http://dx.doi.org/10.18280/isi.270107.
Повний текст джерелаАнотація:
The way we use video streaming is evolving. Users used to broadcast their videos on social media platforms. These platforms enable them to interact from anywhere they want. Recently, there has been a wide range of people who use live video streaming platforms regularly. Thanks to high-speed Internet connections, live video streaming is now easier than ever. Many of these platforms broadcast live video feeds of electronic games, so young streamers use them to make money. Live streaming refers to media that is simultaneously broadcasted and recorded online in real-time. Despite the growing popularity of these platforms, there is a risk that this technology will be abused. Several other recorded cases of abuse have resulted in the emerging popularity of live streaming platforms. Many criminal and public proceedings may rely on information linked to a normal Web user's Online activity. Examining the web browser's history or cache may reveal helpful information about the suspect's activities. The evidence can reveal keys that might lead to this individual being convicted or clear. This work continues what was previously done to reconstruct cached video streams from YouTube and Twitter on Firefox. Our main aim in this paper is to examine data from a cached live stream using YouTube Gaming/Live and Nimo TV on Firefox and Chromium browsers.
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TM, Shashidhar, and K. B. Ramesh. "An efficient computational approach to balance the trade-off between image forensics and perceptual image quality." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (October 1, 2019): 3474. http://dx.doi.org/10.11591/ijece.v9i5.pp3474-3479.
Повний текст джерелаАнотація:
The increasing trends of image processing applications play a very crucial role in the modern-day information propagation with the ease of cost effectiveness. As image transmission or broadcasting is the simplest form communication which determines easy, fastest and effective way of network resource utilization, thereby since past one decade it has gained significant attention among various research communities. As most of the image attributes often contains visual entities corresponding to any individual, hence, exploration and forging of such attributes with malicious intention often leads to social and personal life violation and also causes intellectual property right violation when social media, matrimonial and business applications are concerned. Although an extensive research effort endeavored pertaining to image forensics in the past, but existing techniques lack effectiveness towards maintaining equilibrium in between both image forensics and image quality assessment performances from computational viewpoint. Addressing this limitation associated with the existing system, this proposed study has come up with a novel solution which achieves higher degree of image forensics without compromising the visual perception of an image. The study formulates an intelligent empirical framework which determines cost-effective authentication of an image object from both complexity and quality viewpoint. Finally, the study also presented a numerical simulation outcome to ensure the performance efficiency of the system.
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Afzal, Asmara, Mehdi Hussain, Shahzad Saleem, M. Khuram Shahzad, Anthony T. S. Ho, and Ki-Hyun Jung. "Encrypted Network Traffic Analysis of Secure Instant Messaging Application: A Case Study of Signal Messenger App." Applied Sciences 11, no. 17 (August 24, 2021): 7789. http://dx.doi.org/10.3390/app11177789.
Повний текст джерелаАнотація:
Instant messaging applications (apps) have played a vital role in online interaction, especially under COVID-19 lockdown protocols. Apps with security provisions are able to provide confidentiality through end-to-end encryption. Ill-intentioned individuals and groups use these security services to their advantage by using the apps for criminal, illicit, or fraudulent activities. During an investigation, the provision of end-to-end encryption in apps increases the complexity for digital forensics investigators. This study aims to provide a network forensic strategy to identify the potential artifacts from the encrypted network traffic of the prominent social messenger app Signal (on Android version 9). The analysis of the installed app was conducted over fully encrypted network traffic. By adopting the proposed strategy, the forensic investigator can easily detect encrypted traffic activities such as chatting, media messages, audio, and video calls by looking at the payload patterns. Furthermore, a detailed analysis of the trace files can help to create a list of chat servers and IP addresses of involved parties in the events. As a result, the proposed strategy significantly facilitates extraction of the app’s behavior from encrypted network traffic which can then be used as supportive evidence for forensic investigation.
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Ramirez, Fanny. "The digital divide in the US criminal justice system." New Media & Society 24, no. 2 (February 2022): 514–29. http://dx.doi.org/10.1177/14614448211063190.
Повний текст джерелаАнотація:
The growing use of digital evidence from smartphones and social media has led to a digital divide in the US criminal justice system that advantages law enforcement and prosecutors while further increasing the vulnerability of poor people and people of color who rely on public legal assistance. Drawing on a year-long ethnographic study of one of the first digital forensics laboratories in a public defender office, I argue that digital inclusion in the form of better resources for public defenders is necessary for equitable and fair representation in today’s criminal justice system. Findings show that access to digital forensic technologies is an important equalizing tool that allows public defenders to (1) mount strong, data-driven cases; (2) create counter narratives that challenge depictions of marginalized defendants as dangerous; and (3) engage in nuanced storytelling to highlight the complexities of human relationships and life circumstances that shape cases.
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Irwansyah, Irwansyah, and Helda Yudiastuti. "ANALISIS DIGITAL FORENSIK REKAYASA IMAGE MENGGUNAKAN JPEGSNOOP DAN FORENSICALLY BETA." Jurnal Ilmiah Matrik 21, no. 1 (July 27, 2019): 54–63. http://dx.doi.org/10.33557/jurnalmatrik.v21i1.518.
Повний текст джерелаАнотація:
The development of information technology is not only beneficial for humans, but often also used for negative purposes. Crime by utilizing digital image technology is very easy to do using a computer, so it is not surprising if more and more cases of cybercrime occur. The spread of digital images on social media in the form of images or videos raises public anxiety that these images or videos cannot be considered reliable evidence, because both images and videos can be easily engineered. The purpose of this study is to analyze a digital image that has been manipulated or engineered using a particular software or program. Image manipulation techniques that will be used are: Image splicing, copy-move, and retouching images. While the analysis tool uses the ELA method introduced by Krawetz which is available online from the website (https://29a.ch/photo-forensics/#forensic-magnifier) and Jpegsnoop software.
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Riadi, Imam, Herman, and Nur Hamida Siregar. "Mobile Forensic Analysis of Signal Messenger Application on Android using Digital Forensic Research Workshop (DFRWS) Framework." Ingénierie des systèmes d information 27, no. 6 (December 31, 2022): 903–13. http://dx.doi.org/10.18280/isi.270606.
Повний текст джерелаАнотація:
Cybercrime is a crime committed using equipment connected to the internet. One of the cybercrimes that occured during the COVID-19 pandemic was the spread hoaxes about the COVID-19 vaccine which caused panic in society. Signal Messenger is one of the social media that has become a trending topic since the number of personal data security issues and the emergence of end-to-end encryption features. This research aims to find digital evidence on Signal Messenger application installed on the perpetrator's Android smartphone. This research uses Belkasoft, Magnet AXIOM, and MOBILedit Forensic Express tools and implements the Digital Forensics Research Workshop (DFRWS) framework in each stage of the research experiment. The research was carried out according to the case scenario with 11 predetermined parameters. Digital evidence is found from the Signal Messenger application: application information, account information, chat, pictures, videos, contacts, and stickers. The results of this research indicate that Belkasoft Evidence Center forensic tool is better, with an accuracy rate of 78.69%, while Magnet AXIOM is 26.23% and MOBILedit Forensic Express is 9.84%. The results of this research can be used as a reference for other forensic researchers/experts in handling similar crime cases on the Signal Messenger application to get better results.
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Daulay, Zikri Sulthoni, and Rini Indrayani. "ANALISIS KEAMANAN BROWSER DALAM BERSOSIAL MEDIA MENGGUNAKAN METODE INSTITUTE OF JUSTICE (NIJ)." Djtechno: Jurnal Teknologi Informasi 3, no. 2 (December 30, 2022): 167–75. http://dx.doi.org/10.46576/djtechno.v3i2.2598.
Повний текст джерелаАнотація:
Active users of social media in Indonesia continue to increase every year. But there are still many users who do not understand the security of accessing social media, especially when accessing with a browser. For this reason, the browsers analyzed in this study are the Google Chrome and Mozilla Firefox browsers with two modes, namely public mode and incognito mode. This study aims to identify the level of browser security in using social media in the browser. The method used is the NIJ (National Institute of Justice) methodology. The tool used to get the data is using the FTK Imager 4.5.0.3 application. The results of this study are when accessing social media Facebook, Instagram, Twitter is not safe using Google Chrome and Mozilla Firefox browsers with public mode and incognito mode because user_id, email and some passwords are still detected in the FTK Imager tool. For the percentage results obtained in the study, namely 89% of user_id data, passwords, emails found in public mode Google Chrome browsers, 67% data found in incognito mode Google Chrome browsers, 78% data found in public mode Mozilla Firefox browsers, and 89% of data found in Mozilla Firefox browser incognito mode.Keywords: Live Forensics; Institute of Justice; Browser; Media Sosial; FTK Imager
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Yoon, Yung Han, and Umit Karabiyik. "Forensic Analysis of Fitbit Versa 2 Data on Android." Electronics 9, no. 9 (September 2, 2020): 1431. http://dx.doi.org/10.3390/electronics9091431.
Повний текст джерелаАнотація:
The increase in the adoption of wearable fitness trackers has led to their inclusion as valuable evidence used by law enforcement during investigations. The information available in these fitness trackers can be used by law enforcement to prosecute or exonerate an individual. Wearable fitness devices are constantly being released by companies, with new firmware created for each iteration. As technology developers, research and law enforcement must keep pace to take advantage of data that can be used in investigations. The Fitbit line of devices is a popular brand of wearable trackers. This study will investigate what artifacts are generated by the new Fitbit Versa 2 by investigating what data are generated and stored on the smartphone app component of the new device. The artifacts discovered will be related to areas of forensic interest that are relevant to a law enforcement officer or digital forensics practitioner. Previous research and their methodologies used for application and mobile forensics will be used to conduct this research. This study finds the Fitbit Versa 2, and by extension, the Fitbit smartphone application does not store social media message notifications pushed to the tracker by the user’s mobile device. Some credit card information, health-related data, such as heart rate, GPS locations, and other potentially identifying data were found in plaintext. While the exposed data is not enough on its own to pose an immediate serious issue, it can be used as leverage to phish a user for further details.
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ADHI, I. PUTU KRISNA. "REKAMAN ELEKRONIK PERSONAL CHAT PADA SOCIAL MEDIA SEBAGAI ALAT BUKTI." Media Iuris 1, no. 3 (December 18, 2018): 457. http://dx.doi.org/10.20473/mi.v1i3.9829.
Повний текст джерелаАнотація:
Abstract:This journal is titled "Personal Chat Electronic Record on Social Media as a Proof Tool". The problem formulation of this journal contains how a Personal Chat can be used as a legitimate evidence in front of the court seen from Indonesia's positive law and also the comparison of some personal chat features on some social media that can be used as valid evidence in court. This writing uses a normative legal research method by linking various sources related to the validity of the Personal Chat as a valid proof. The reason for using normative due to the obscurity of norms in national rules regarding the verification of Personal Chat in court. The conclusion of this journal is in accordance with the Republic of Indonesia Number 19 of 2016 concerning Amendments to Law Number 11 of 2008 concerning Information and Electronic Transactions which will then be referred to as the ITE Law, Electronic Information and / or Electronic Documents and / or results the print is a valid legal proof, and this Personal Chat is a proof of evidence that the Personal Chat as a proof cannot stand alone. The requirement for Personal Chat to become evidence in the trial is that it has fulfilled the formal and material requirements, accompanied by expert information or digital forensics, fulfills the verification of authentication and also the necessity of merging with other evidence as a provision for the minimum principle of evidence. Regarding the use of personal chat as a legitimate means of proof it is also not immediately obtained from various social media, but from several social media applications that have fulfilled the standardization of authenticity and security guarantees.Keywords: Electronic Recordings, Personal Chat, Social Media, Digital Evidence.Abstrak:Jurnal ini berjudul "Rekaman Elektronik Personal Chat Pada Social Media Sebagai Alat Bukti". Rumusan masalah jurnal ini berisikan tentang bagaimana suatu Personal Chat tersebut dapat dijadikan sebagai alat bukti yang sah dimuka pengadilan dilihat dari hukum positif Indonesia dan juga komparasi dari beberapa fitur personal chat pada beberapa social media yang dapat dijadikan alat bukti yang sah dimuka persidangan. Penulisan ini menggunakan metode penelitian hukum normatif dengan mengaitkan berbagai sumber yang berkaitan dengan keabsahan Personal Chat tersebut sebagai alat bukti yang sah. Alasan mempergunakan normatif dikarenakan kekaburan norma dalam aturan nasional mengenai pembuktian Personal Chat di dalam pengadilan. Kesimpulan dari jurnal ini yaitu sesuai dengan -Undang Republik Indonesia Nomor 19 Tahun 2016 Tentang Perubahan Atas Undang-Undang Nomor 11 Tahun 2008 Tentang Informasi Dan Transaksi Elektronik yang selanjutnya akan disebut Undang-Undang ITE, Informasi Elektronik dan/atau Dokumen Elektronik dan/atau hasil cetaknya merupakan alat bukti hukum yang sah, serta Personal Chat ini sebagai alat bukti petunjuk dimana Personal Chat sebagai alat bukti tidak dapat berdiri sendiri. Syarat agar Personal Chat menjadi alat bukti dalam persidangan adalah telah memenuhi syarat formil dan materiil, disertai oleh keterangan ahli atau digital forensik, memenuhi kasifikasi otentifikasi dan juga keharusan penggabungan dengan alat bukti lain sebagai sebuah ketentuan adanya prinsip minimum alat bukti. Mengenai penggunaan personal chat sebagai alat bukti yang sah juga tidak serta-merta didapat dari berbagai social media akan tetapi dari beberapa aplikasi social media yang sudah memenuhi standarisasi otentisitas dan jaminan keamanan.Kata kunci : Rekaman Elektronik, Personal Chat, Social Media, Alat Bukti.
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Bérubé, Maxime, Thuc-Uyên Tang, Francis Fortin, Sefa Ozalp, Matthew L. Williams, and Pete Burnap. "Social media forensics applied to assessment of post–critical incident social reaction: The case of the 2017 Manchester Arena terrorist attack." Forensic Science International 313 (August 2020): 110364. http://dx.doi.org/10.1016/j.forsciint.2020.110364.
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Saputri, Novi, and Rini Indrayani. "ANALISIS DATA FORENSIK INVESTIGASI KASUS PEREDARAN NARKOBA PADA SMARTPHONE BERBASIS ANDROID." Djtechno: Jurnal Teknologi Informasi 3, no. 2 (December 30, 2022): 156–66. http://dx.doi.org/10.46576/djtechno.v3i2.2597.
Повний текст джерелаАнотація:
Along with the development of Smartphone technology, especially Android-based which is a communication tool whose features develop from time to time with a total of 89.2% of users, which is also followed by an increase in users of the WhatsApp Instant Messaging Platform. WhatsApp is one of the most popular social media in the world with a total of 2.20 billion users. On the other hand, WhatsApp is often used as a medium of crime (cybercrime) such as the case of narcotics trafficking, whose transactions are carried out online by sending messages, pictures, videos, locations and so on. The purpose of this study is to find forensic evidence and to compare two tools using the (Without Root Access) and (Root Access) approaches, using the NIJ (National Institute of Justice) method. The results of the extraction were then analyzed using the forensic tools Magnet Axiom without Rooting access managed to obtain data extraction of 33.33% while MobilEdit forensics was equal to a total of 33.33%. While the comparison with Rooting access, Magnet Axiom obtained greater data extraction as much as 77.77% and MobilEdit Forensic as much as 66.66%. The results of the study based on the scenario used, it can be concluded that the recommended tool is Magnet Axiom because it has better performance
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Rowe, Neil C., Simson L. Garfinkel, Robert Beverly, and Panayotis Yannakogeorgos. "Challenges in Monitoring Cyberarms Compliance." International Journal of Cyber Warfare and Terrorism 1, no. 2 (April 2011): 35–48. http://dx.doi.org/10.4018/ijcwt.2011040104.
Повний текст джерелаАнотація:
A cyberweapon can be as dangerous as any weapon. Fortunately, recent technology now provides some tools for cyberweapons control. Digital forensics can be done on computers seized during or after hostilities. Cyberweapons differ significantly from other software, especially during development, and recent advances in summarizing the contents of storage media can locate possible cyberweapons quickly. Use of cyberweapons can be distinguished in the usual malicious Internet traffic by being aimed at targets associated with political, social, and cultural issues that are often known in advance, and those targets can then be monitored. Cyberweapons are relatively unreliable compared to other kinds of weapons because they are susceptible to flaws in software; therefore, cyberweapons require considerable testing, preferably against live targets. Thus, international “cyberarms agreements” could provide for forensics on cyberweapons and usage monitoring. Agreements also encourage more responsible cyberweapons use by stipulating attribution and reversibility. The authors discuss the kinds of international agreements that are desirable, and examine the recent interest of the U.S. government in such agreements.
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Ulloa, Carlos, Dora M. Ballesteros, and Diego Renza. "Video Forensics: Identifying Colorized Images Using Deep Learning." Applied Sciences 11, no. 2 (January 6, 2021): 476. http://dx.doi.org/10.3390/app11020476.
Повний текст джерелаАнотація:
In recent years there has been a significant increase in images and videos circulating in social networks and media, edited with different techniques, including colorization. This has a negative impact on the forensic field because it is increasingly difficult to discern what is original content and what is fake. To address this problem, we propose two models (a custom architecture and a transfer-learning-based model) based on CNNs that allows a fast recognition of the colorized images (or videos). In the experimental test, the effect of three hyperparameters on the performance of the classifier were analyzed in terms of HTER (Half Total Error Rate). The best result was found for the Adam optimizer, with a dropout of 0.25 and an input image size of 400 × 400 pixels. Additionally, the proposed models are compared with each other in terms of performance and inference times and with some state-of-the-art approaches. In terms of inference times per image, the proposed custom model is 12x faster than the transfer-learning-based model; however, in terms of precision (P), recall and F1-score, the transfer-learning-based model is better than the custom model. Both models generalize better than other models reported in the literature.
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Wilson-Kovacs, Dana. "Digital media investigators: challenges and opportunities in the use of digital forensics in police investigations in England and Wales." Policing: An International Journal 44, no. 4 (May 7, 2021): 669–82. http://dx.doi.org/10.1108/pijpsm-02-2021-0019.
Повний текст джерелаАнотація:
PurposeIn-depth knowledge about specific national approaches to using digital evidence in investigations is scarce. A clearer insight into the organisational barriers and professional challenges experienced, alongside a more detailed picture of how digital evidence can help police investigations are required to empirically substantiate claims about how digital technologies are changing the face of criminal investigations. The paper aims to focus on the introduction of digital media investigators to support investigating officers with the collection and interpretation of digital evidence.Design/methodology/approachDrawing on ethnographic and interview data collected as part of an Economic and Social Research Council-funded project on the application of digital forensics expertise in policing in England and Wales, this paper examines the changing face of investigations in relation to escalating digital demand.FindingsThe analysis presents the national and regional organisational parameters of deploying digital expertise in criminal investigation and examines some of the challenges of being a digital media investigator (DMI). Through testimonies from DMIs, digital forensic practitioners, investigating and senior officers and forensic managers, the analysis explores the organisational tensions in the collection, processing, interpretation and use of information from digital devices for evidential purposes.Research limitations/implicationsThe paper offers an empirical basis for the comparative study of how the DMI role has been implemented by law enforcement agencies and its fit within broader institutional considerations and processes.Practical implicationsThe development of the DMI role has raised questions about the supply of digital expertise, especially to volume crime investigations, and tensions around occupational divisions between scientific and operational units.Social implicationsThe findings show that while the introduction of the DMI role was much needed, the development of this valuable provision within each force and the resources available require sustained and coordinated support to protect these professionals and retain their skills.Originality/valueThis study contributes to the growing sociological and criminological literature with an ethnographically based perspective into the organisational and occupational tensions in the identification and processing of digital evidence in England and Wales.
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Lu, Yujiang, Yaju Liu, Jianwei Fei, and Zhihua Xia. "Channel-Wise Spatiotemporal Aggregation Technology for Face Video Forensics." Security and Communication Networks 2021 (August 27, 2021): 1–13. http://dx.doi.org/10.1155/2021/5524930.
Повний текст джерелаАнотація:
Recent progress in deep learning, in particular the generative models, makes it easier to synthesize sophisticated forged faces in videos, leading to severe threats on social media about personal privacy and reputation. It is therefore highly necessary to develop forensics approaches to distinguish those forged videos from the authentic. Existing works are absorbed in exploring frame-level cues but insufficient in leveraging affluent temporal information. Although some approaches identify forgeries from the perspective of motion inconsistency, there is so far not a promising spatiotemporal feature fusion strategy. Towards this end, we propose the Channel-Wise Spatiotemporal Aggregation (CWSA) module to fuse deep features of continuous video frames without any recurrent units. Our approach starts by cropping the face region with some background remained, which transforms the learning objective from manipulations to the difference between pristine and manipulated pixels. A deep convolutional neural network (CNN) with skip connections that are conducive to the preservation of detection-helpful low-level features is then utilized to extract frame-level features. The CWSA module finally makes the real or fake decision by aggregating deep features of the frame sequence. Evaluation against a list of large facial video manipulation benchmarks has illustrated its effectiveness. On all three datasets, FaceForensics++, Celeb-DF, and DeepFake Detection Challenge Preview, the proposed approach outperforms the state-of-the-art methods with significant advantages.
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Ahmad, Muhammad Hazim, Ahmad Syukran Baharuddin, Hasnizam Hashim, Ruqayyah Razak, Nurul Syahirah Saharudin, and Syaril Nizam Omar. "FORENSIC EVIDENCE AS A MEAN OF PROOF IN DEVELOPING PRIMA FACIE CASE IN TAKHBIB CRIMINAL OFFENCE." UUM Journal of Legal Studies 13, No.1 (January 31, 2022): 221–48. http://dx.doi.org/10.32890/uumjls2022.13.1.10.
Повний текст джерелаАнотація:
A third party’s intervention has been one of the most significant factors in Malaysian divorce cases. Third parties may come from family members and non-family members. This interference is called takhbīb. Within the scope of Malaysian Syariah criminal law, tahkbib is regarded as a criminal offence. However, it is difficult to prove this criminal offence. None of the Syariah law journals reported cases that could be used as reference or case studies. This article proposes a method of proof, which is practical and can be carried out in the Syariah courts to prove the criminal offence of takhbīb. In gathering and compiling the necessary data and related materials, this qualitative study embraced document analysis as a research method. These data are inductively evaluated by implementing qualitative content analysis. This study showed several obstacles in the development of a prima facie prosecution by the Syarie Public Prosecutor, including the absence of eyewitnesses present as evidence. Third-party intrusion is commonly committed through social networks such as WhatsApp, Telegram, WeChat, and Facebook Messenger. The use of such media networks as a medium of contact may also be brought as part of the evidence before the Syariah courts. The best mechanism to be implemented in this case is by using digital forensics and expert opinion. The digital forensic investigator will track or archive the communications from the social media, and deliver them in the form of a written text. In terms of proving the commission of takhbīb criminal offence, this study contributes to the improvement of the Syariah legal system. In short, the law still provides a method of proving criminal offences. Any legal practitioner should make good use of statutory provisions instead of suggesting amendments to it.
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Rodriguez-Ortega, Yohanna, Dora M. Ballesteros, and Diego Renza. "Copy-Move Forgery Detection (CMFD) Using Deep Learning for Image and Video Forensics." Journal of Imaging 7, no. 3 (March 20, 2021): 59. http://dx.doi.org/10.3390/jimaging7030059.
Повний текст джерелаАнотація:
With the exponential growth of high-quality fake images in social networks and media, it is necessary to develop recognition algorithms for this type of content. One of the most common types of image and video editing consists of duplicating areas of the image, known as the copy-move technique. Traditional image processing approaches manually look for patterns related to the duplicated content, limiting their use in mass data classification. In contrast, approaches based on deep learning have shown better performance and promising results, but they present generalization problems with a high dependence on training data and the need for appropriate selection of hyperparameters. To overcome this, we propose two approaches that use deep learning, a model by a custom architecture and a model by transfer learning. In each case, the impact of the depth of the network is analyzed in terms of precision (P), recall (R) and F1 score. Additionally, the problem of generalization is addressed with images from eight different open access datasets. Finally, the models are compared in terms of evaluation metrics, and training and inference times. The model by transfer learning of VGG-16 achieves metrics about 10% higher than the model by a custom architecture, however, it requires approximately twice as much inference time as the latter.
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Vizoso, Ángel, Martín Vaz-Álvarez, and Xosé López-García. "Fighting Deepfakes: Media and Internet Giants’ Converging and Diverging Strategies Against Hi-Tech Misinformation." Media and Communication 9, no. 1 (March 3, 2021): 291–300. http://dx.doi.org/10.17645/mac.v9i1.3494.
Повний текст джерелаАнотація:
Deepfakes, one of the most novel forms of misinformation, have become a real challenge in the communicative environment due to their spread through online news and social media spaces. Although fake news have existed for centuries, its circulation is now more harmful than ever before, thanks to the ease of its production and dissemination. At this juncture, technological development has led to the emergence of deepfakes, doctored videos, audios or photos that use artificial intelligence. Since its inception in 2017, the tools and algorithms that enable the modification of faces and sounds in audiovisual content have evolved to the point where there are mobile apps and web services that allow average users its manipulation. This research tries to show how three renowned media outlets—<em>The Wall Street Journal</em>,<em> The Washington Post</em>,<em> </em>and<em> Reuters</em>—and three of the biggest Internet-based companies—Google, Facebook, and Twitter—are dealing with the spread of this new form of fake news. Results show that identification of deepfakes is a common practice for both types of organizations. However, while the media is focused on training journalists for its detection, online platforms tended to fund research projects whose objective is to develop or improve media forensics tools.
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Xia, Zhiming, Tong Qiao, Ming Xu, Xiaoshuai Wu, Li Han, and Yunzhi Chen. "Deepfake Video Detection Based on MesoNet with Preprocessing Module." Symmetry 14, no. 5 (May 5, 2022): 939. http://dx.doi.org/10.3390/sym14050939.
Повний текст джерелаАнотація:
With the development of computer hardware and deep learning, face manipulation videos represented by Deepfake have been widely spread on social media. From the perspective of symmetry, many forensics methods have been raised, while most detection performance might drop under compression attacks. To solve this robustness issue, this paper proposes a Deepfake video detection method based on MesoNet with preprocessing module. First, the preprocessing module is established to preprocess the cropped face images, which increases the discrimination among multi-color channels. Next, the preprocessed images are fed into the classic MesoNet. The detection performance of proposed method is verified on two datasets; the AUC on FaceForensics++ can reach 0.974, and it can reach 0.943 on Celeb-DF which is better than the current methods. More importantly, even in the case of heavy compression, the detection rate can still be more than 88%.
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Iuliani, Massimo, Marco Fontani, Dasara Shullani, and Alessandro Piva. "Hybrid reference-based Video Source Identification." Sensors 19, no. 3 (February 5, 2019): 649. http://dx.doi.org/10.3390/s19030649.
Повний текст джерелаАнотація:
Millions of users share images and videos generated by mobile devices with different profiles on social media platforms. When publishing illegal content, they prefer to use anonymous profiles. Multimedia Forensics allows us to determine whether videos or images have been captured with the same device, and thus, possibly, by the same person. Currently, the most promising technology to achieve this task exploits unique traces left by the camera sensor into the visual content. However, image and video source identification are still treated separately from one another. This approach is limited and anachronistic, if we consider that most of the visual media are today acquired using smartphones that capture both images and videos. In this paper we overcome this limitation by exploring a new approach that synergistically exploits images and videos to study the device from which they both come. Indeed, we prove it is possible to identify the source of a digital video by exploiting a reference sensor pattern noise generated from still images taken by the same device. The proposed method provides performance comparable with or even better than the state-of-the-art, where a reference pattern is estimated from video frames. Finally, we show that this strategy is effective even in the case of in-camera digitally stabilized videos, where a non-stabilized reference is not available, thus solving the limitations of the current state-of-the-art. We also show how this approach allows us to link social media profiles containing images and videos captured by the same sensor.
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Bernacki, Jarosław. "Robustness of digital camera identification with convolutional neural networks." Multimedia Tools and Applications 80, no. 19 (July 7, 2021): 29657–73. http://dx.doi.org/10.1007/s11042-021-11129-y.
Повний текст джерелаАнотація:
AbstractThis paper considers the area of digital forensics (DF). One of the problem in DF is the issue of identification of digital cameras based on images. This aspect has been attractive in recent years due to popularity of social media platforms like Facebook, Twitter etc., where lots of photographs are shared. Although many algorithms and methods for digital camera identification have been proposed, there is lack of research about their robustness. Therefore, in this paper the robustness of digital camera identification with the use of convolutional neural network is discussed. It is assumed that images may be of poor quality, for example, degraded by Poisson noise, Gaussian blur, random noise or removing pixels’ least significant bit. Experimental evaluation conducted on two large image datasets (including Dresden Image Database) confirms usefulness of proposed method, where noised images are recognized with almost the same high accuracy as normal images.
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Turner, Adam, and Angela Samantha Maitland Irwin. "Bitcoin transactions: a digital discovery of illicit activity on the blockchain." Journal of Financial Crime 25, no. 1 (January 2, 2018): 109–30. http://dx.doi.org/10.1108/jfc-12-2016-0078.
Повний текст джерелаАнотація:
Purpose The purpose of this paper is to determine if Bitcoin transactions could be de-anonymised by analysing the Bitcoin blockchain and transactions conducted through the blockchain. In addition, graph analysis and the use of modern social media technology were examined to determine how they may help reveal the identity of Bitcoin users. A review of machine learning techniques and heuristics was carried out to learn how certain behaviours from the Bitcoin network could be augmented with social media technology and other data to identify illicit transactions. Design/methodology/approach A number of experiments were conducted and time was spend observing the network to ascertain how Bitcoin transactions work, how the Bitcoin protocol operates over the network and what Bitcoin artefacts can be examined from a digital forensics perspective. Packet sniffing software, Wireshark, was used to see whether the identity of a user is revealed when they set up a wallet via an online wallet service. In addition, a block parser was used to analyse the Bitcoin client synchronisation and reveal information on the behaviour of a Bitcoin node when it joins the network and synchronises to the latest blockchain. The final experiment involved setting up and witnessing a transaction using the Bitcoin Client API. These experiments and observations were then used to design a proof of concept and functional software architecture for searching, indexing and analyzing publicly available data flowing from the blockchain and other big data sources. Findings Using heuristics and graph analysis techniques show us that it is possible to build up a picture of behaviour of Bitcoin addresses and transactions, then utilise existing typologies of illicit behaviour to collect, process and exploit potential red flag indicators. Augmenting Bitcoin data, big data and social media may be used to reveal potentially illicit financial transaction going through the Bitcoin blockchain and machine learning applied to the data sets to rank and cluster suspicious transactions. Originality/value The development of a functional software architecture that, in theory, could be used to detect suspicious illicit transactions on the Bitcoin network.
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Dhar, Ankita, Himadri Mukherjee, Shibaprasad Sen, Md Obaidullah Sk, Amitabha Biswas, Teresa Gonçalves, and Kaushik Roy. "Author Identification from Literary Articles with Visual Features: A Case Study with Bangla Documents." Future Internet 14, no. 10 (September 23, 2022): 272. http://dx.doi.org/10.3390/fi14100272.
Повний текст джерелаАнотація:
Author identification is an important aspect of literary analysis, studied in natural language processing (NLP). It aids identify the most probable author of articles, news texts or social media comments and tweets, for example. It can be applied to other domains such as criminal and civil cases, cybersecurity, forensics, identification of plagiarizer, and many more. An automated system in this context can thus be very beneficial for society. In this paper, we propose a convolutional neural network (CNN)-based author identification system from literary articles. This system uses visual features along with a five-layer convolutional neural network for the identification of authors. The prime motivation behind this approach was the feasibility to identify distinct writing styles through a visualization of the writing patterns. Experiments were performed on 1200 articles from 50 authors achieving a maximum accuracy of 93.58%. Furthermore, to see how the system performed on different volumes of data, the experiments were performed on partitions of the dataset. The system outperformed standard handcrafted feature-based techniques as well as established works on publicly available datasets.
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Anggraini, Nenny, Siti Ummi Masruroh, and Hapsari Tiaraningtias. "Analisa Forensik Whatsapp Messanger Pada Smartphone Android." Jurnal Ilmiah FIFO 12, no. 1 (July 16, 2020): 83. http://dx.doi.org/10.22441/fifo.2020.v12i1.008.
Повний текст джерелаАнотація:
Abstract Internet technology and smartphones are increasingly rapidly followed by the rise of social media users, especially instant messaging that can be accessed using a smartphone, especially Android. One of the problems of social media is cyber crime that utilizes social media. Based on data from Instant Checkmate in 2014, 30,000 websites were hacked, and 12 casualties fell within a fraction of the crime from fraud to sex crimes, and it occurs in cyber crime involving social media, including instant media WhatsApp messenger. So it takes the forensic digital process to look for evidence of the crime, because basically there is no crime that does not leave a trace. This study was conducted to find the forensic evidence on the WhatsApp messenger application accessed on Android smartphones. WhatsApp messenger was chosen because it used to reach 1.5 billion users from over 2.7 billion users of social media worldwide. In this study, the simulation method used in the study to run 15 scenarios, including the return of the deleted files, the search for forensic evidence such as name and account number, a list of names and contact numbers, group chat, and text messages, pictures, video, and document files on personal chat, then text messages, pictures, videos, document files, voice notes, and location in group chat. The results of this study indicate that almost all forensic evidence traces in the WhatsApp messenger application are found, but the URL media can not be opened because it is encrypted by WhatsApp. Keyword: Digital Forensic, Forensic Evidence, Smartphone, WhatsApp Messenger. Abstrak Perkembangan teknologi internet dan smartphone yang semakin pesat diikuti pula oleh meningkatnya pengguna media social pada instant messager yang diakses menggunakan smartphone khususnya Android. salah satu permasalahan yang tidak luput dari media sosial adalah tindak kejahatan dunia maya yang memanfaatkan media sosial. Berdasarkan data dari Instant Checkmate pada tahun 2014 sebanyak 30.000 website diretas, dan 12 korban perdetik berjatuhan dari berbagai aspek kejahatan dari penipuan hingga kejahatan seks, dan hal tersebut terjadi dalam praktek kejahatan internet (cyber crime) melibatkan media sosial, termasuk media instant messanger WhatsApp. Sehingga diperlukannya proses digital forensik untuk mencari bukti-bukti kejahatan tersebut, karena pada dasarnya tidak ada kejahatan yang tidak meninggalkan jejak. Penelitian ini dilakukan untuk menemukan bukti-bukti forensik tersebut pada aplikasi WhatsApp messanger yang diakses pada smartphone Android. WhatsApp messanger dipilih karena digunakan mencapai 1,5 tiliyun user dari lebih dari 2,7 triliyun pengguna media sosial seluruh dunia. Pada penelitian ini, metode simulasi digunakan dalam penelitian dengan menjalankan 15 skenario, diantaranya adalah pengembalian file yang dihapus, pencarian bukti forensik berupa nama dan nomor akun, daftar nama dan nomor kontak, group chat, kemudian pesan teks, gambar, video, dan file dokumen pada personal chat, kemudian pesan teks, gambar, video, file dokumen, voice note, dan location pada group chat. Hasil dari penelitian ini menunjukkan bahwa hampir semua jejak bukti forensik pada aplikasi WhatsApp messanger berhasil ditemukan, namun media URL tidak dapat dibuka karena terenkripsi oleh WhatsApp.Keyword: Bukti Forensik, Digital Forensik, Smartphone, WhatsApp Messanger.