Thematische Bibliographien / Mobile forensic tools

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Auswahl der wissenschaftlichen Literatur zum Thema „Mobile forensic tools“

Autor: Grafiati

Veröffentlicht am 25. Juni 2021

Zuletzt aktualisiert am 1. Februar 2022

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Zeitschriftenartikel zum Thema "Mobile forensic tools"

Sachdeva, Shaweta, B. L. Raina und Avinash Sharma. „Analysis of Digital Forensic Tools“. Journal of Computational and Theoretical Nanoscience 17, Nr. 6 (01.06.2020): 2459–67. http://dx.doi.org/10.1166/jctn.2020.8916.

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This paper aims to analyze different tools for Forensic Data Analysis comes under the branch of Digital Forensics. Forensic data analysis is done with digital techniques. Digital forensics becomes more important in law enforcement, due to the large use of computers and mobile devices. The pattern recognition system most appropriately fits into the Analysis Phase of the Digital Forensics. Pattern Recognition involves two processes. One Process is an analysis and the second process is recognition. The result of the analysis is taken out of the attributes from the patterns to be recognized i.e., a pattern of different faces and fingerprints. These attributes are then utilized for the further process in the analysis phase which provides attention on various techniques of pattern recognition that are applied to digital forensic examinations and is proposed to develop different forensic tools to collect evidence that would be helpful to solve specific types of crimes. This evidence further helps the examiner in the analysis phase of the digital forensic process by identifying the applicable data.

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Osho, Oluwafemi, und Sefiyat Oyiza Ohida. „Comparative Evaluation of Mobile Forensic Tools“. International Journal of Information Technology and Computer Science 8, Nr. 1 (08.01.2016): 74–83. http://dx.doi.org/10.5815/ijitcs.2016.01.09.

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Hikmatyar, Firmansyah Gustav, und Bambang Sugiantoro. „Digital Forensic Analysis on Android Smartphones for Handling Cybercrime Cases“. IJID (International Journal on Informatics for Development) 7, Nr. 2 (07.01.2019): 19. http://dx.doi.org/10.14421/ijid.2018.07204.

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As the times progressed, forensic science has developed rapidly. The science of forensics extends to new areas of technology ranging from digital forensics, computer forensics and mobile forensics. Mobile forensics in analyzing and collecting data is obtained from various resources, such as operating systems, communication lines and also various storage media. The most popular mobile operating system of the day is a smartphone based on android operating system. With android technology, criminals can use that technology as a crime medium ranging from overriding crime ideas, crime targets and crime scenarios. In this Final Project use forensic mobile application to get data residing in cell phone actors, in the form of text, sound, picture and video that have or not yet deleted in smartphone. In this study, a model for investigating the crime scene is the author using the Generic Computer Forensic Investigation Model (GCFIM). On the GCFIM model the investigator may be able to return to the previous stage because of the possibility of a changeable situation (both physical and digital), the investigation tools used, the crime tools used, and the level of investigative expertise. In this research also added weighting method of word TF-IDF, where this method can help to find keyword in digital evidence in the form of word / text.

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Curran, Kevin, Andrew Robinson, Stephen Peacocke und Sean Cassidy. „Mobile Phone Forensic Analysis“. International Journal of Digital Crime and Forensics 2, Nr. 3 (Juli 2010): 15–27. http://dx.doi.org/10.4018/jdcf.2010070102.

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During the past decade, technological advances in mobile phones and the development of smart phones have led to increased use and dependence on the mobile phone. The explosion of its use has led to problems such as fraud, criminal use and identity theft, which have led to the need for mobile phone forensic analysis. In this regard, the authors discuss mobile phone forensic analysis, what it means, who avails of it and the software tools used.

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Riadi, Imam, Anton Yudhana und Mushab Al Barra. „Forensik Mobile pada Layanan Media Sosial LinkedIn“. JISKA (Jurnal Informatika Sunan Kalijaga) 6, Nr. 1 (20.01.2021): 9–20. http://dx.doi.org/10.14421/jiska.2021.61-02.

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The research explores mobile forensic on LinkedIn social media. Forensic mobile finds digital evidence of job hoax cases in LinkedIn, investigation using the NIST (National Institute of Standard and Technology) method. Data collection techniques using Andriller tools in investigations. Data examination using tools Root Browser, Autopsy in the forensic process. data analysis using tools MOBILedit in the forensic process. The investigation found digital evidence of log activity, a status update on LinkedIn. Other results found in the investigation are 17 WiFi password, 117 download history, 263 phone calls, 1 file deleted, 1 file hidden, and 1 file raised, the research has reached the expected target.

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Umar, Rusydi, Imam Riadi und Guntur Maulana Zamroni. „Mobile Forensic Tools Evaluation for Digital Crime Investigation“. International Journal on Advanced Science, Engineering and Information Technology 8, Nr. 3 (20.06.2018): 949. http://dx.doi.org/10.18517/ijaseit.8.3.3591.

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Arévalo Ortega, Yamir Alexander, Sonia Rocio Corredor Vargas und Gustavo Adolfo Higuera Castro. „Forensic analysis with hacking tools on android devices“. Visión electrónica 13, Nr. 1 (31.01.2019): 162–77. http://dx.doi.org/10.14483/22484728.14405.

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Currently, the use of mobile terminals is becoming a necessity for a high number of people around the world which has driven the development of devices with Android operating system; In addition to this, the same indiscriminate access to resources of internet and weak local and international regulations on the use, they have become vulnerable to attacks on the network - injection of malware, ransomware-, among many others. Therefore, this article reviews the hacking tools for the forensic investigation of mobile terminals, proposing from the documentary research a forensic information acquisition model to determine tangible and significant evidences as a probative material.

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Zamroni, Guntur M., und Imam Riadi. „Mobile Forensic Tools Validation and Evaluation for Instant Messaging“. International Journal on Advanced Science, Engineering and Information Technology 10, Nr. 5 (15.10.2020): 1860. http://dx.doi.org/10.18517/ijaseit.10.5.7499.

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Nizam, Syafiqah Hanisah Shahrol, Nurul Hidayah Ab Rahman und Niken Dwi Wahyu Cahyani. „Keyword Indexing And Searching Tool (KIST): A Tool to Assist the Forensics Analysis of WhatsApp Chat“. International Journal on Information and Communication Technology (IJoICT) 6, Nr. 1 (20.06.2020): 23. http://dx.doi.org/10.21108/ijoict.2020.61.481.

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Digital forensics is a field that concerned with finding and presenting evidence sourced from digital devices, such as computers and mobile phones. Most of the forensic analysis software is proprietary, and eventually, specialized analysis software is developed in both the private and public sectors. This paper presents an alternative of forensic analysis tools for digital forensics, which specifically to analyze evidence through keyword indexing and searching. Keyword Indexing and Searching Tool (KIST) is proposed to analyze evidence of interest from WhatsApp chat text files using keyword searching techniques and based on incident types. The tool was developed by adopting the Prototyping model as its methodology. KIST includes modules such as add, edit, remove, display the indexed files, and to add WhatsApp chat text files. Subsequently, the tool is tested using functionality testing and user testing. Functionality testing shows all key functions are working as intended, while users testing indicates the majority of respondents are agree that the tool is able to index and search keyword and display forensic analysis results.

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Ghannam, Hussein Abed. „Forensic Analysis of Artifacts of Giant Instant Messaging “WhatsApp” in Android Smartphone“. Journal of Applied Information, Communication and Technology 5, Nr. 2 (28.10.2018): 73–83. http://dx.doi.org/10.33555/ejaict.v5i2.55.

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WhatsApp is a giant mobile instant message IM application with over 1billion users. The huge usage of IM like WhatsApp through giant smart phone “Android” makes the digital forensic researchers to study deeply. The artefacts left behind in the smartphone play very important role in any electronic crime, or any terror attack. “WhatsApp” as a biggest IM in the globe is considered to be very important resource for information gathering about any digital crime. Recently, end-to-end encryption and many other important features were added and no device forensic analysis or network forensic analysis studies have been performed to the time of writing this paper. This paper explains how can we able to extract the Crypt Key of “WhatsApp” to decrypt the databases and extract precious artefacts resides in the android system without rooting the device. Artefacts that extracted from the last version of WhatsApp have been analysed and correlate to give new valuable evidentiary traces that help in investigating. Many hardware and software tools for mobile and forensics are used to collect as much digital evidence as possible from persistent storage on android device. Some of these tools are commercial like UFED Cellebrite and Andriller, and other are open source tools such as autopsy, adb, WhatCrypt. All of these tools that forensically sound accompanied this research to discover a lot of artefacts resides in android internal storage in WhatsApp application.

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Dissertationen zum Thema "Mobile forensic tools"

Shakir, Amer, Muhammad Hammad und Muhammad Kamran. „Comparative Analysis & Study of Android/iOS MobileForensics Tools“. Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-44797.

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This report aims to draw a comparison between two commercial mobile forensics and recovery tools, Magnet AXIOM and MOBILedit. A thorough look at previously done studies was helpful to know what aspects of the data extractions must be compared and which areas are the most important ones to focus upon. This work focuses on how the data extracted from one tool compares with another and provides comprehensive extraction based on different scenarios, circumstances, and aspects. Performances of both tools are compared based on various benchmarks and criteria. This study has helped establish that MOBILedit has been able to outperform Magnet AXIOM on more data extraction and recovery aspects. It is a comparatively better tool to get your hands on.

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(8800973), Kelsey Billups. „New and Emerging Mobile Apps Among Teens - Are Forensic Tools Keeping Up?“ Thesis, 2020.

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Mobile applications are an important but fast changing piece of the digital forensics’ world. For mobile forensics researchers and field analysts, it is hard to keep up with the pace of the ever-changing world of the newest and most popular applications teens are using. Mobile forensic tools are quickly becoming more and more supportive of new applications, but with how quickly apps are changing and new ones being released, it is still difficult for the tools to keep up. The research question for this project examines to what extent digital forensic tools support new and emerging applications seen recently in investigations involving teenagers? For this research, a survey was conducted asking digital forensic analysts, and others who investigate digital crimes, what applications they are coming across most frequently during investigations involving teens and whether those applications are being supported by forensic tools. The top three applications from the survey that were not supported by mobile forensic tools, Monkey, Houseparty, and Likee were populated onto a test device and then evaluated and analyzed to see what forensic artifacts were found in those applications. The mobile application artifacts were then compared on two different forensic tools to see which tool obtains the most forensic artifacts from the applications. Through the examination and analysis of the applications and data contained within the apps, it was determined that 61% of the populated forensic artifacts were recovered manually and only 45% were recovered by a forensic tool for the Monkey application. 100% of the populated forensic artifacts were recovered manually and only 29% were recovered by a forensic tool for the Houseparty application. 42% of the populated forensic artifacts were recovered manually and only 3% were recovered by a forensic tool for the Likee application. It was found that the extent of support from digital forensic tools for these types of applications depends greatly on how the application stores the artifacts, but the artifact extraction support was limited for all applications. This research benefits in helping researchers and analysts by understanding the data and artifacts contained within the applications, what forensic artifacts are recoverable, and where to find those important artifacts. This research can help in finding important evidence for future investigations.

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Pin, Chang Feng, und 鄭鋒濱. „A Study on the Differences of Capturing Digital Evidence by Forensic Tools Based on Mobile Device Platform“. Thesis, 2014. http://ndltd.ncl.edu.tw/handle/75964868104108420059.

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碩士
國防大學
資訊管理學系
103
With the popularity of mobile devices and Internet use, crime information network has been significantly improved, the crime scene is no longer limited to physical traces card crime, law enforcement officers with traditional forensic equipment and tools are insufficient to capture Internet digital space scene evidence.Therefore, law enforcement officers are required to understand the extent of the platform for mobile devices, such as electromagnetic records which may be generated, which will not get the record, what tools should be used to carry out forensic,it’s their basic knowledge. In response to the investigation of crime and improve smartphone efficiency and detection rate, investigators must be able to promptly identify and trace the source of the problem and, through compliance with standard operating procedures, evidence collection and processing so that come with digital evidence in court evidence probative force and enhance the professionalism of the forensic report and credibility. Thus, for different smartphone platforms crime patterns, what type of digital evidence should capture and use what professional forensic tools in order to effectively and quickly for digital forensic evidence, as court evidence in the courts has become very important. and how to provide an appropriate recommendations or guidelines for the use of law enforcement personnel reference, has become very urgent and important issues worth exploring. This study attempts to create a different smartphone platforms use the same context, and the use of different professional forensic tools implementation, by sorting, classification, analysis and other steps to retrieve the digital evidence to compare the implementation of key differences, such as the mirror file produced time, file restore time, the identification data integrity, data identification readability, data identification number, to restore the hardware and software categories and support system, expect to obtain an objective relative differences in data, and then for different smartphones platform crime patterns, what type of digital evidence should capture and use what professional forensic tools in order to effectively and quickly for digital forensic evidence put forward appropriate recommendations or guidelines related to law enforcement officers to serve for reference use; study showed relevant information is available forensic personnel familiar with the operation and forensic tools to be an effective reference for the court, and proposed future direction for the development of resistance and forensic work.

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Chou, Po-How, und 邱柏豪. „The study on the capturing digital evidence by forensic tools with enterprise mobility management encryption application based on mobile device“. Thesis, 2018. http://ndltd.ncl.edu.tw/handle/9j4589.

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碩士
國立交通大學
管理學院資訊管理學程
106
Recently, the development of information technology and the mobile devices, whether it is in the work, school or various applications in life, it is inseparable from mobile devices and digital information content. The applications developed by mobile devices are widely used in daily life and also used in different fields, including medical, information processing, biometrics, financial transactions, navigation and positioning, and information science. The most popular applications for mobile are communication and email. However, the applications use in phishing, scams, or theft of data. The information-intensive environment, when a digital criminal record is to be verified, it is necessary for a professional digital forensic tool to verify it. However, the rapid development of information security and digital forensics has provided evidence of more evidence and credibility for the standardization and technology of digital forensics in the future. The encrypting applications from mobile, extracting sent and received letters and enterprise applications developed by the company, using digital forensics tools to process and retrieve feature information to identify the correctness of the source and verify the information extracted by the encrypted application. And indirectly understand whether it can provide evidence of favorable evidence and credibility. In the experiments of this paper, test results were obtained through the same forensic tools, mobile device systems, and encryption applications. In summary, the research results show that the evidence ability and credibility evidence provided by the digital forensic tools can be applied legally. However, the encrypted application can protect the enterprise data without being accessed by special permission or tools. And provide the correct digital evidence.

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Bücher zum Thema "Mobile forensic tools"

Mikhaylov, Igor. Mobile Forensics Cookbook: Data acquisition, extraction, recovery techniques, and investigations using modern forensic tools. Packt Publishing - ebooks Account, 2017.

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Buchteile zum Thema "Mobile forensic tools"

Agrawal, Animesh Kumar, Pallavi Khatri und Sumitra Ranjan Sinha. „Comparative Study of Mobile Forensic Tools“. In Advances in Data and Information Sciences, 39–47. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8360-0_4.

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Alhassan, J. K., R. T. Oguntoye, Sanjay Misra, Adewole Adewumi, Rytis Maskeliūnas und Robertas Damaševičius. „Comparative Evaluation of Mobile Forensic Tools“. In Proceedings of the International Conference on Information Technology & Systems (ICITS 2018), 105–14. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73450-7_11.

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Gupchup, Nirneeta, und Nishchol Mishra. „A Systematic Survey on Mobile Forensic Tools Used for Forensic Analysis of Android-Based Social Networking Applications“. In Data, Engineering and Applications, 205–15. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6351-1_16.

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Shukla, Utkarsha, Bishwas Mandal und K. V. D. Kiran. „Perlustration on Mobile Forensics Tools“. In Computer Networks and Inventive Communication Technologies, 1225–31. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9647-6_97.

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Wang, Ping, Matt Rosenberg und Hubert D’Cruze. „Integration of Mobile Forensic Tool Capabilities“. In Advances in Intelligent Systems and Computing, 81–87. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77028-4_13.

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Satheesh Kumar, S., Bibin Thomas und K. L. Thomas. „An Agent Based Tool for Windows Mobile Forensics“. In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 77–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35515-8_7.

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Saleem, Shahzad, Oliver Popov und Oheneba Kwame Appiah-Kubi. „Evaluating and Comparing Tools for Mobile Device Forensics Using Quantitative Analysis“. In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 264–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39891-9_17.

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Kemp, Karen, und Subrata Acharya. „Towards the Design of a Forensic Tool for Mobile Data Visualization“. In Lecture Notes in Computer Science, 462–70. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91521-0_33.

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Lai, Yenting, Chunghuang Yang, Chihhung Lin und TaeNam Ahn. „Design and Implementation of Mobile Forensic Tool for Android Smart Phone through Cloud Computing“. In Convergence and Hybrid Information Technology, 196–203. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24106-2_26.

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Curran, Kevin, Andrew Robinson, Stephen Peacocke und Sean Cassidy. „Mobile Phone Forensic Analysis“. In Crime Prevention Technologies and Applications for Advancing Criminal Investigation, 250–62. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-1758-2.ch016.

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Konferenzberichte zum Thema "Mobile forensic tools"

Narayanan, A. Sankara, und M. Mohamed Ashik. „Computer Forensic First Responder Tools“. In 2012 International Conference on Advances in Mobile Network, Communication and its Applications (MNCAPPS). IEEE, 2012. http://dx.doi.org/10.1109/mncapps.2012.38.

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Padmanabhan, Radhika, Karen Lobo, Mrunali Ghelani, Dhanika Sujan und Mahesh Shirole. „Comparative analysis of commercial and open source mobile device forensic tools“. In 2016 Ninth International Conference on Contemporary Computing (IC3). IEEE, 2016. http://dx.doi.org/10.1109/ic3.2016.7880238.

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Alief, Fahdiaz, Yohan Suryanto, Linda Rosselina und Tofan Hermawan. „Analysis of Autopsy Mobile Forensic Tools against Unsent Messages on WhatsApp Messaging Application“. In 2020 7th International Conference on Electrical Engineering, Computer Sciences and Informatics (EECSI). IEEE, 2020. http://dx.doi.org/10.23919/eecsi50503.2020.9251876.

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Cristian, Pozo-Calderon, Torres-Carrion Hernan, Guaman-Quinche Rene, Alvarez-Pineda Francisco und Narvaez-Guillen Cristian. „Methodologies and Forensic Analysis Tools on Android Mobile Devices: A Systematic Literature Review“. In 2020 15th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, 2020. http://dx.doi.org/10.23919/cisti49556.2020.9140852.

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Zareen, Amjad, und Shamim Baig. „Notice of Violation of IEEE Publication Principles: Mobile Phone Forensics: Challenges, Analysis and Tools Classification“. In 2010 Fifth International Workshop on Systematic Approaches to Digital Forensic Engineering (SADFE). IEEE, 2010. http://dx.doi.org/10.1109/sadfe.2010.24.

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Lwin, Htar Htar, Wai Phyo Aung und Kyaw Kyaw Lin. „Comparative Analysis of Android Mobile Forensics Tools“. In 2020 IEEE Conference on Computer Applications (ICCA). IEEE, 2020. http://dx.doi.org/10.1109/icca49400.2020.9022838.

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Wilson, Rodney, und Hongmei Chi. „A Case Study for Mobile Device Forensics Tools“. In ACM SE '17: SouthEast Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3077286.3077564.

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Yates, Maynard. „Practical investigations of digital forensics tools for mobile devices“. In 2010 Information Security Curriculum Development Conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1940941.1940972.

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Ninawe, Prashant N., und Shrikant B. Ardhapurkar. „Design and implementation of cloud based mobile forensic tool“. In 2015 International Conference on Innovations in Information,Embedded and Communication Systems (ICIIECS). IEEE, 2015. http://dx.doi.org/10.1109/iciiecs.2015.7193033.

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Catanese, Salvatore Amato, und Giacomo Fiumara. „A visual tool for forensic analysis of mobile phone traffic“. In the 2nd ACM workshop. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1877972.1877992.

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Berichte der Organisationen zum Thema "Mobile forensic tools"

Mentsiev, A., und M. T. Alams. Mobile forensic tools and techniques: Android data security. Ljournal, 2019. http://dx.doi.org/10.18411/2019-2019-2019-00002.

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