Relevant bibliographies by topics / Forensic analysis

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Forensic analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 January 2023

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Journal articles on the topic "Forensic analysis"

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Sachdeva, Shaweta, B. L. Raina, and Avinash Sharma. "Analysis of Digital Forensic Tools." Journal of Computational and Theoretical Nanoscience 17, no. 6 (June 1, 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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Antwi, Paul. "Device Information for Forensic Analysis." Advances in Multidisciplinary and scientific Research Journal Publication 1, no. 1 (July 26, 2022): 373–78. http://dx.doi.org/10.22624/aims/crp-bk3-p59.

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This document provides an overview of information for forensic analysis related to device name, serial number and model of devices used to connect to social networking platforms. The increasing use of social networking applications on smartphones makes these devices a gold mine for forensic researchers. Potential evidence can be captured on these devices and recovered with the right tools and research methods. The increasing proliferation of network devices in homes and buildings increases the possibilities of finding digital traces relevant to an investigation, physical or virtual: cyber-attacks, identity theft, etc. connected to the network can also find useful traces on the devices themselves found or stored in an associated cloud account that can be identified by device ID, model, and serial number. Keywords: Digital Forensics; Device Information, Evidence, Storage, Cyber forensics framework. BOOK Chapter ǀ Research Nexus in IT, Law, Cyber Security & Forensics. Open Access. Distributed Free Citation: Paul Antwi (2022): Device Information for Forensic Analysis Book Chapter Series on Research Nexus in IT, Law, Cyber Security & Forensics. Pp 373-378 www.isteams.net/ITlawbookchapter2022. dx.doi.org/10.22624/AIMS/CRP-BK3-P59
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Dodoo, Herbert Cyril. "Deep Learning (DL) Oriented Forensic Analysis." Advances in Multidisciplinary and scientific Research Journal Publication 1, no. 1 (July 26, 2022): 321–28. http://dx.doi.org/10.22624/aims/crp-bk3-p51.

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Cyber-attacks are now more prevalent than ever before in all aspects of our daily lives. As a result of this circumstance, both individuals and organizations are fighting cybercrime on a regular basis. Furthermore, today's hackers have advanced a step further and are capable of employing complex cyber-attack strategies, exacerbating the problem. Some of these approaches are minute and undetectable, and they frequently masquerade as genuine requests and directives. To combat this threat, cyber security professionals, as well as digital forensic investigators, are constantly compelled to filter through massive and complicated pools of data, also known as Big Data, in order to uncover Potential Digital Forensic Evidence. that can be used as evidence in court. Potential Digital Evidence can then be used to assist investigators in reaching certain conclusions and/or judgments. The fact that Big Data frequently comes from various sources and has diverse file formats makes cyber forensics even more difficult for investigators. When it comes to the processing of vast amounts of complicated data for forensic purposes, forensic investigators typically have less time and budget to fulfil the rising demands. This paper will be studying how to incorporate Deep Learning cognitive computing approaches into Cyber Forensics Keywords: Deep Learning, Forensic Analysis, Artificial Intelligence, Online Safety, Evidence BOOK Chapter ǀ Research Nexus in IT, Law, Cyber Security & Forensics. Open Access. Distributed Free Citation: Herbert Cyril Dodoo (2022): Deep Learning (DL) Oriented Forensic Analysis Book Chapter Series on Research Nexus in IT, Law, Cyber Security & Forensics. Pp 320-328 www.isteams.net/ITlawbookchapter2022. dx.doi.org/10.22624/AIMS/CRP-BK3-P51
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Sabillon, Regner, Jordi Serra-Ruiz, Victor Cavaller, and Jeimy J. Cano. "Digital Forensic Analysis of Cybercrimes." International Journal of Information Security and Privacy 11, no. 2 (April 2017): 25–37. http://dx.doi.org/10.4018/ijisp.2017040103.

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This paper reviews the existing methodologies and best practices for digital investigations phases like collecting, evaluating and preserving digital forensic evidence and chain of custody of cybercrimes. Cybercriminals are adopting new strategies to launch cyberattacks within modified and ever changing digital ecosystems, this article proposes that digital investigations must continually readapt to tackle cybercrimes and prosecute cybercriminals, working in international collaboration networks, sharing prevention knowledge and lessons learned. The authors also introduce a compact cyber forensics model for diverse technological ecosystems called Cyber Forensics Model in Digital Ecosystems (CFMDE). Transferring the knowledge, international collaboration, best practices and adopting new digital forensic tools, methodologies and techniques will be hereinafter paramount to obtain digital evidence, enforce organizational cybersecurity policies, mitigate security threats, fight anti-forensics practices and indict cybercriminals. The global Digital Forensics community ought to constantly update current practices to deal with cybercriminality and foreseeing how to prepare to new technological environments where change is always constant.
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Lee, Sang Young. "Mobile Digital Forensics Framework for Smartphone User Analysis." Webology 19, no. 1 (January 20, 2022): 4335–51. http://dx.doi.org/10.14704/web/v19i1/web19285.

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Blockchain-based digital forensics technology is an efficient way to prevent forgery/modulation of evidence including collecting and analyzing evidential data using the technology in compliance with smartphone forensics procedures after a smartphone is seized. Moreover, the use of large-capacity storage devices and various digital devices have become a realistic solution for its development of IT in situations where the existing digital forensics analysis methods are regarded as limitations. This paper analyzed user’s status on smartphone application and implemented a smartphone user analysis framework that may extract significant digital evidence in a digital forensic way based on a blockchain perspective. In this paper researched a system that may provide important information to digital forensic analysts through these frameworks. It is expected that the proposed system will be expanded by much more structured data and online unstructured data such as SNS reports.
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Qureshi, Sirajuddin, Jianqiang Li, Faheem Akhtar, Saima Tunio, Zahid Hussain Khand, and Ahsan Wajahat. "Analysis of Challenges in Modern Network Forensic Framework." Security and Communication Networks 2021 (August 28, 2021): 1–13. http://dx.doi.org/10.1155/2021/8871230.

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Network forensics can be an expansion associated with network security design which typically emphasizes avoidance and detection of community assaults. It covers the necessity for dedicated investigative abilities. When you look at the design, this indeed currently allows investigating harmful behavior in communities. It will help organizations to examine external and community this is undoubtedly around. It is also important for police force investigations. Network forensic techniques can be used to identify the source of the intrusion and the intruder’s location. Forensics can resolve many cybercrime cases using the methods of network forensics. These methods can extract intruder’s information, the nature of the intrusion, and how it can be prevented in the future. These techniques can also be used to avoid attacks in near future. Modern network forensic techniques face several challenges that must be resolved to improve the forensic methods. Some of the key challenges include high storage speed, the requirement of ample storage space, data integrity, data privacy, access to IP address, and location of data extraction. The details concerning these challenges are provided with potential solutions to these challenges. In general, the network forensic tools and techniques cannot be improved without addressing these challenges of the forensic network. This paper proposed a thematic taxonomy of classifications of network forensic techniques based on extensive. The classification has been carried out based on the target datasets and implementation techniques while performing forensic investigations. For this purpose, qualitative methods have been used to develop thematic taxonomy. The distinct objectives of this study include accessibility to the network infrastructure and artifacts and collection of evidence against the intruder using network forensic techniques to communicate the information related to network attacks with minimum false-negative results. It will help organizations to investigate external and internal causes of network security attacks.
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Adeyemi, Ikuesan R., Shukor Abd Razak, and Nor Amira Nor Azhan. "A Review of Current Research in Network Forensic Analysis." International Journal of Digital Crime and Forensics 5, no. 1 (January 2013): 1–26. http://dx.doi.org/10.4018/jdcf.2013010101.

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Establishing facts on cyber crime is gradually gaining wider relevance in prosecuting cyber criminals. The branch of cyber policing saddled with this responsibility is the network forensic community (researchers, developer, and investigator). However, the recurring rate of advances in cybercrime poses greater challenge to the available improvements in network forensics analysis tools (NFAT) as well as to investigators, and ultimately, researchers. The need for an efficient cutting-edge research finding in curbing network crimes therefore is undeniably critical. This paper describes the distinction between network security and network forensics. In addition, the authors identify factors that militate against most network forensic techniques as well as the research challenges in network forensics. Furthermore, the paper discusses on the current research works on network forensics analysis. This research is useful to the research community of network forensics, for knowledge on existing research techniques, and direction on further research in network forensics.
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Sukamto, Pria, Ispandi, Arman Syah Putra, Nurul Aisyah, and Rohmat Toufiq. "Forensic Digital Analysis for CCTV Video Recording." International Journal of Science, Technology & Management 3, no. 1 (January 22, 2022): 284–91. http://dx.doi.org/10.46729/ijstm.v3i1.460.

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The background of this research is how to make a video that can be analyzed as forensic data to prove the truth of the video, therefore with forensics it can be used as evidence if the video contains incorrect data or contains data capable of crime so that it can be used as data forensics. The method used in this study is to use the literature review method which uses the basis of many previous studies. From journals and books based on similar research, so that it can help develop existing problems to the latest problems so that they can find novelty in this research. The problem raised in this research is how to make a video from a CCTV that can be proven, by certain methods in order to make the video as forensic data, that can be proven so that it can be developed into data containing crimes that can be used as evidence. The purpose of this study is how to find the right method in order to analyze a CCTV video, so that it can be used as evidence on forensic data with the NIST method, it can be proven that this method is the right method in analyzing a video, so that it can be used as evidence and as data forensics.
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Hikmatyar, Firmansyah Gustav, and Bambang Sugiantoro. "Digital Forensic Analysis on Android Smartphones for Handling Cybercrime Cases." IJID (International Journal on Informatics for Development) 7, no. 2 (January 7, 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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Asamoah, Jonas Takyi. "Exploring Lack of Due Diligence as a Threat to Forensic Analysis Preparation and Readiness." Advances in Multidisciplinary and scientific Research Journal Publication 1 (July 26, 2022): 307–14. http://dx.doi.org/10.22624/aims/crp-bk3-p49.

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The usage of digital technology in the digital forensic investigation has grown in tandem with the rising importance of technology today. Too many incidences of digital and physical crime which is the focus of the world nowadays. To gather the finest evidence and investigative outcomes, a digital forensic model must be established. This study included a review of the literature on digital forensics and models established in digital forensics. According to the findings, the majority of research involves broad inquiries and procedures that overlap. Furthermore, no model has been developed to design a systemic inquiry. In this study, we propose a methodology for digital forensic examination to address this issue. This model combines several of the previous models and adds some new variables that are relevant to the study. Keywords: Due Diligence, Threats, Forensic Analysis, Preparation, Readiness, Cyber Security, BOOK Chapter ǀ Research Nexus in IT, Law, Cyber Security & Forensics. Open Access. Distributed Free Citation: Jonas Takyi Asamoah (2022): Exploring Lack of Due Diligence as a Threat to Forensic Analysis Preparation and Readiness Book Chapter Series on Research Nexus in IT, Law, Cyber Security & Forensics. Pp 307-314 www.isteams.net/ITlawbookchapter2022. dx.doi.org/10.22624/AIMS/CRP-BK3-P49
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Dissertations / Theses on the topic "Forensic analysis"

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Fairbanks, Kevin D. "Forensic framework for honeypot analysis." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/33977.

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The objective of this research is to evaluate and develop new forensic techniques for use in honeynet environments, in an effort to address areas where anti-forensic techniques defeat current forensic methods. The fields of Computer and Network Security have expanded with time to become inclusive of many complex ideas and algorithms. With ease, a student of these fields can fall into the thought pattern of preventive measures as the only major thrust of the topics. It is equally important to be able to determine the cause of a security breach. Thus, the field of Computer Forensics has grown. In this field, there exist toolkits and methods that are used to forensically analyze production and honeypot systems. To counter the toolkits, anti-forensic techniques have been developed. Honeypots and production systems have several intrinsic differences. These differences can be exploited to produce honeypot data sources that are not currently available from production systems. This research seeks to examine possible honeypot data sources and cultivate novel methods to combat anti-forensic techniques. In this document, three parts of a forensic framework are presented which were developed specifically for honeypot and honeynet environments. The first, TimeKeeper, is an inode preservation methodology which utilizes the Ext3 journal. This is followed with an examination of dentry logging which is primarily used to map inode numbers to filenames in Ext3. The final component presented is the initial research behind a toolkit for the examination of the recently deployed Ext4 file system. Each respective chapter includes the necessary background information and an examination of related work as well as the architecture, design, conceptual prototyping, and results from testing each major framework component.
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Rodríguez, Mariela, and James Winefordner. "Elemental Forensic Analysis of Glass." Revista de Química, 2007. http://repositorio.pucp.edu.pe/index/handle/123456789/99672.

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Existe una constante migración de la dependencia de mediciones de propiedades fisicas tales como índice de refracción y densidad hacia métodos de análisis elemental de trazas en la identificación de vidrios como evidencia forense. Numerosas técnicas espectroscópicas, radioquímicas, y de espectrometría de masa han sido aplicadas al análisis multielemental de pequeños trozos de vidrio. Esta revisión presenta algunos de los métodos más comúnmente empleados junto con sus ventajas y limitaciones.
At identifying glass as forensic evidence, there is a continued move away from dependence on physical properties measured, such as index of refraction and density, towards methods of elemental analysis of its traces. Several spectroscopic, radiochemical and mass spectrometry techniques have been applied for multielemental analysis of small samples of glass. This review shows some of the most commonly used methods, as well as their advantages and limitations.
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Gettings, Katherine Butler. "Forensic Ancestry and Phenotype SNP Analysis and Integration with Established Forensic Markers." Thesis, The George Washington University, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3590467.

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When an evidential DNA profile does not match identified suspects or profiles from available databases, further DNA analyses targeted at inferring the possible ancestral origin and phenotypic characteristics of the perpetrator could yield valuable information. Single Nucleotide Polymorphisms (SNPs), the most common form of genetic polymorphisms, have alleles associated with specific populations and/or correlated to physical characteristics. With this research, single base primer extension (SBE) technology was used to develop a 50 SNP assay designed to predict ancestry among the primary U.S. populations (African American, East Asian, European, and Hispanic/Native American), as well as pigmentation phenotype. The assay has been optimized to a sensitivity level comparable to current forensic DNA analyses, and has shown robust performance on forensic-type samples. In addition, three prediction models were developed and evaluated for ancestry in the U.S. population, and two models were compared for eye color prediction, with the best models and interpretation guidelines yielding correct information for 98% and 100% of samples, respectively. Also, because data from additional DNA markers (STR, mitochondrial and/or Y chromosome DNA) may be available for a forensic evidence sample, the possibility of including this data in the ancestry prediction was evaluated, resulting in an improved prediction with the inclusion of STR data and decreased performance when including mitochondrial or Y chromosome data. Lastly, the possibility of using next-generation sequencing (NGS) to genotype forensic STRs (and thus, the possibility of a multimarker multiplex incorporating all forensic markers) was evaluated on a new platform, with results showing the technology incapable of meeting the needs of the forensic community at this time.

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Nilsson, Martina. "Mitochondrial DNA in Sensitive Forensic Analysis." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-7458.

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Shah, Jayna J. "Microfluidic devices for forensic DNA analysis." Fairfax, VA : George Mason University, 2007. http://hdl.handle.net/1920/2878.

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Thesis (Ph. D.)--George Mason University, 2007.
Title from PDF t.p. (viewed Jan. 22, 2008). Thesis director: Rao V. Mulpuri. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Electrical and Computer Engineering. Vita: p. 159. Includes bibliographical references (p. 145-158). Also available in print.
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Ogwu, John. "Forensic pharmaceutical analysis of counterfeit medicines." Thesis, De Montfort University, 2018. http://hdl.handle.net/2086/17552.

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The World Health Organisation suggests that falsified and substandard medicines (FSMs) constitute approximately 10% of medicines globally with higher figures expected in low and middle income countries (LMICs). To combat the proliferation of FSMs, this study is aimed at developing simple and rapid instrumental methods for the identification and quantification of these medicines. Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy, Raman spectroscopy and two probe Mass Spectrometry (MS) methods were assessed for the rapid screening of tablet dosage forms. These systems were chosen because NO solvent extraction of the sample was required. Comparison with analyses of the tablets by accepted but more time consuming methods (UV-Vis and LC-MS) assessed the quality of the data obtained. Analgesic/antipyretic and antimalarial medicines tablet dosage forms are commonly falsified and for this study tablets were obtained opportunistically from different countries around the world. Reference spectra of appropriate active pharmaceutical ingredients (APIs) and excipients were created, for each method, as part of the identification process. Currently only Raman and ATR-FTIR delivered quantitative results which were based on automated multivariate analysis. For tablets with a single API, Raman and ATR-FTIR provided the simplest route to API confirmation and for tablets with multiple APIs or APIs present at < 10%w/w, in the tablet, probe MS methods were superior. Quantitative screening using ATR-FTIR required the samples to be weighed and crushed to produce reproducible data. Comparison of API confirmation tests between trial methods and LC-MS showed complete agreement and the quantitative results were within ±15% of the UV-Vis data. Each of the new tests can be completed in under five minutes and a survey of 69 paracetamol tablets, from around the world, showed that 10% were suspect. Subsequent probe MS showed the presence of a second undeclared API in different samples. More complex tablet formulations, for example the antimalarials were difficult to quantify rapidly. Raman and PCA methods provide a rapid approach to tablet identification within a limited range of possibilities. Factors that may affect Raman spectra of tablets include the expected API, the API levels, different excipients, colours or surface coatings for the tablets. The simplicity, speed and cost effectiveness of the proposed analytical methods make them suitable for use in LMICs. The potential use of these simple analytical methods in addition to already established pharmacopoeia approved (solvent extraction) techniques could help provide more comprehensive data about FSMs globally.
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van, den Berg Jelle, and Filip Lagerholm. "Forensic Analysis of the Nintendo Switch." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-42451.

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In this thesis, we did a forensic analysis of a Nintendo Switch gaming console. It is both a portable and a stationary device, which makes it so that it could contain valuable information about the usage of the console at home and elsewhere. Multiple methods of data extraction were used, including using an exploit to obtain storage memory, extracting the contents of the SD card and capturing network traffic. The findings from the analysis of these data sources were compared to the information on the user interface. Any information that could not be found on the user interface was reported. The main findings of memory analysis were a detailed log file of user interactions, JSON files with personal information such as email addresses, and crash logs with information about the state of the console during the crash. The SD card mainly contains screenshots with embedded timestamps, and the network capture does not contain any forensically relevant information. The combination of these different types of information could makethe Nintendo Switch a useful source of evidence during an investigation.
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Lu, Andy. "Forensic analysis on wireless medical devices." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2022. https://ro.ecu.edu.au/theses/2541.

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The number of Internet of Things (IoT) devices is forecast to grow to over 25 billion by 2030, with the healthcare IoT market projected to grow to 25.9% of IoT devices by 2028 worldwide. However, with new and growing technologies come new types of risks. Current risk assessment and risk management methods haven’t been designed to anticipate or predict these risks. IoT risks relate to openness and lack of standardisation, linking and connectivity between the devices and the lack of skilled support for IoT devices and networks. These factors put medical IoT devices and, by extension, their users at risk from cyber threats. Additionally, the attack surface for the medical IoT has not been fully mapped, nor have the risks been fully assessed. The lack of coverage means increased risk for manufacturers, medical facilities, and potentially, patients. This project evaluates the effectiveness of how new and emerging wireless and connected medical devices can be managed and analysed through a digital forensic framework. An initial analysis of the currently available frameworks showed that they did not address the nuances of implementing a wireless or connected medical device into a healthcare organisation. Digital forensic frameworks that were deemed relevant to wireless medical devices were selected and tested against several currently available wireless medical devices. Four frameworks were tested across four devices each. The outcome was that none of the frameworks was fully able to effectively manage wireless medical devices (at least in terms of the objectives of digital forensics), with each missing elements that would aid an investigator or a hospital organisation in the case of a cyber-related incident. These results led to the synthesis and testing of a framework that addressed the missing elements. The framework emphasises forensic readiness planning and risk management. The synthesised framework was tested against a new device. The results of the test found that the synthesised framework was effective in both the proactive digital forensics approach and reactive approach. The testing found that the framework performed better than the other tested frameworks, containing additional phases and steps that were advantageous in preparing and reacting to incidents involving wireless medical devices.
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Eide, Jarle, and Jan Ove Skogheim Olsen. "Forensic analysis of an unknown embedded device." Thesis, Norges Teknisk-Naturvitenskaplige Universitet, Institutt for datateknikk og informasjonsvitenskap, 2006. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-10060.

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Every year thousands of new digital consumer device models come on the market. These devices include video cameras, photo cameras, computers, mobile phones and a multitude of different combinations. Most of these devices have the ability to store information in one form or another. This is a problem for law enforcement agencies as they need access to all these new kinds of devices and the information on them in investigations. Forensic analysis of electronic and digital equipment has become much more complex lately because of the sheer number of new devices and their increasing internal technological sophistication. This thesis tries to help the situation by reverse engineering a Qtek S110 device. More specifically we analyze how the storage system of this device, called the object store, is implemented on the device’s operating system, Windows Mobile. We hope to figure out how the device stores user data and what happens to this data when it is "deleted". We further try to define a generalized methodology for such forensic analysis of unknown digital devices. The methodology takes into account that such analysis will have to be performed by teams of reverse-engineers more than single individuals. Based on prior external research we constructed and tested the methodology successfully. We were able to figure our more or less entirely the object store’s internal workings and constructed a software tool called BlobExtractor that can extract data, including "deleted", from the device without using the operating system API. The main reverse engineering strategies utilized was black box testing and disassembly. We believe our results can be the basis for future advanced recovery tools for Windows Mobile devices and that our generalized reverse engineering methodology can be utilized on many kinds of unknown digital devices.

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Edlund, Hanna. "Sensitive Identification Tools in Forensic DNA Analysis." Doctoral thesis, Uppsala universitet, Institutionen för genetik och patologi, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-131904.

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DNA as forensic evidence is valuable in criminal investigations. Implementation of new, sensitive and fast technologies is an important part of forensic genetic research. This thesis aims to evaluate new sensitive methods to apply in forensic DNA analysis including analysis of old skeletal remains. In Paper I and II, two novel systems for analysis of STRs, based on the Pyrosequencing technology, are presented. In Paper I, Y chromosomal STRs are analysed. Markers on the male specific Y chromosome are especially useful in analysis of DNA mixtures. In Paper II, ten autosomal STRs are genotyped. The systems are based on sequencing of STR loci instead of size determination of STR fragments as in routine analysis. This provides a higher resolution since sequence variants within the repeats can be detected. Determination of alleles is based on a termination recognition base. This is the base in the template strand that is excluded from the dispensation order in the sequencing of the complementary strand and therefore terminates the reaction. Furthermore, skeletal remains are often difficult to analyse, due to damaging effects from the surrounding environment on the DNA and the high risk of exogenous contamination. Analysis of mitochondrial DNA is useful on degraded samples and in Paper III, mtDNA analysis of 700 years old skeletal remains is performed to investigate a maternal relationship. The quantity and quality of DNA are essential in forensic genetics. In Paper IV the efficiency of DNA isolation is investigated. Soaking skeletal remains in bleach is efficient for decontamination but result in a lower DNA yield, especially on pulverised skull samples. In conclusion, this thesis presents novel sequencing systems for accurate and fast analysis of STR loci that can be useful in evaluation of new loci and database assembly as well as the utility of mtDNA in forensic genetics.
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Books on the topic "Forensic analysis"

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Rudin, Norah. Forensic DNA analysis: Protocols in forensic science. Boca Raton, FL: CRC, 2002.

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Belair, Robert R. Forensic DNA analysis: Issues. Washington, D.C: U.S. Dept. of Justice, Office of Justice Programs, Bureau of Justice Statistics, 1991.

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File system forensic analysis. Boston, Mass: Addison-Wesley, 2005.

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SQL server forensic analysis. Upper Saddle River, NJ: Addison-Wesley, 2008.

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F, Dunn Patrick, ed. Uncertainty analysis for forensic science. 2nd ed. Tucson, Ariz: Lawyers & Judges Pub., 2009.

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Fairgrieve, Scott I. Forensic cremation recovery and analysis. Boca Raton: Taylor & Francis, 2008.

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Eoghan, Casey, ed. Windows forensic analysis: DVD toolkit. 2nd ed. Burlington, MA: Syngress Pub., 2009.

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Brach, Raymond M. Uncertainty analysis for forensic science. 2nd ed. Tucson, Ariz: Lawyers & Judges Pub., 2009.

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Hamilton, Sue L. DNA analysis: Forensic fluids & follicles. Edina, Minn: ABDO Pub. Co., 2008.

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Taroni, Franco, Silvia Bozza, Alex Biedermann, Paolo Garbolino, and Colin Aitken. Data Analysis in Forensic Science. Chichester, UK: John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470665084.

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Book chapters on the topic "Forensic analysis"

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Resano, Martín, and Frank Vanhaecke. "Forensic Applications." In Isotopic Analysis, 391–418. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2012. http://dx.doi.org/10.1002/9783527650484.ch14.

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Lorenzini, Rita, and Luisa Garofalo. "Wildlife Forensics: DNA Analysis in Wildlife Forensic Investigations." In Forensic DNA Analysis, 357–84. Includes bibliographical references and index.: Apple Academic Press, 2020. http://dx.doi.org/10.1201/9781003043027-16.

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Finnigan, Pete. "Forensic Analysis." In Oracle Incident Response and Forensics, 155–75. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-3264-4_5.

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Zięba-Palus, Janina, and Maria Kała. "Forensic Analytics." In Handbook of Trace Analysis, 281–329. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-19614-5_11.

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DiMaggio, John A., and Wesley Vernon. "Forensic Gait Analysis." In Forensic Podiatry, 103–15. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-61737-976-5_6.

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Dettmeyer, Reinhard B., Marcel A. Verhoff, and Harald F. Schütz. "Forensic DNA Analysis." In Forensic Medicine, 357–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38818-7_22.

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Joshi, R. C., and Emmanuel S. Pilli. "Network Forensic Analysis." In Computer Communications and Networks, 107–29. London: Springer London, 2016. http://dx.doi.org/10.1007/978-1-4471-7299-4_6.

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Prinz, Mechthild, and Ruediger Lessig. "Forensic DNA Analysis." In Handbook of Forensic Medicine, 1141–83. Oxford, UK: John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118570654.ch63.

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Bartick, Edward G. "Criminal Forensic Analysis." In Infrared and Raman Spectroscopy in Forensic Science, 87–109. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119962328.ch4.

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López-Monroy, A. Pastor, Hugo Jair Escalante, Manuel Montes-y-Gómez, and Xavier Baró. "Forensic Analysis Recognition." In Engineering Data-Driven Adaptive Trust-based e-Assessment Systems, 1–18. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29326-0_1.

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Conference papers on the topic "Forensic analysis"

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McKay, Christine, Ashwin Swaminathan, Hongmei Gou, and Min Wu. "Image acquisition forensics: Forensic analysis to identify imaging source." In ICASSP 2008 - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/icassp.2008.4517945.

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Wesevich, James W., and Douglas B. Olson. "Explosion Forensic Analysis." In Structures Congress 2005. Reston, VA: American Society of Civil Engineers, 2005. http://dx.doi.org/10.1061/40753(171)249.

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Singh, Kumar Shanu, Annie Irfan, and Neelam Dayal. "Cyber Forensics and Comparative Analysis of Digital Forensic Investigation Frameworks." In 2019 4th International Conference on Information Systems and Computer Networks (ISCON). IEEE, 2019. http://dx.doi.org/10.1109/iscon47742.2019.9036214.

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Ghabban, Fahad M., Ibrahim M. Alfadli, Omair Ameerbakhsh, Amer Nizar AbuAli, Arafat Al-Dhaqm, and Mahmoud Ahmad Al-Khasawneh. "Comparative Analysis of Network Forensic Tools and Network Forensics Processes." In 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE). IEEE, 2021. http://dx.doi.org/10.1109/icscee50312.2021.9498226.

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Whitehurst, Frederic. "Forensic analysis of explosives." In Critical Review Collection. SPIE, 1992. http://dx.doi.org/10.1117/12.141391.

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Edwards, Thomas R. "Forensic video image analysis." In Enabling Technologies for Law Enforcement and Security, edited by John Hicks, Peter R. De Forest, and Vivian M. Baylor. SPIE, 1997. http://dx.doi.org/10.1117/12.266311.

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Peisert, Sean, Sidney Karin, Matt Bishop, and Keith Marzullo. "Principles-driven forensic analysis." In the 2005 workshop. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1146269.1146291.

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Iqbal, Asif, Johannes Olegard, Ranjana Ghimire, Shirin Jamshir, and Andrii Shalaginov. "Smart Home Forensics: An Exploratory Study on Smart Plug Forensic Analysis." In 2020 IEEE International Conference on Big Data (Big Data). IEEE, 2020. http://dx.doi.org/10.1109/bigdata50022.2020.9378183.

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Ataei, Hossein, and Abdel-Salam M. Niazy. "Buckling Analysis of Arched Structures Using Finite Element Analysis." In Seventh Congress on Forensic Engineering. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784479711.080.

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Nelson, Erik L., Deepak Ahuja, Stewart M. Verhulst, and Erin Criste. "Roof Collapse: Forensic Uplift Failure Analysis." In Fourth Forensic Engineering Congress. Reston, VA: American Society of Civil Engineers, 2006. http://dx.doi.org/10.1061/40853(217)47.

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Reports on the topic "Forensic analysis"

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Vaughan, Phillip, Golnar Nabizadeh, Laura Findlay, Heather Doran, Niamh Nic Daeid, and Mark Brown. Understanding Forensic Gait Analysis #1. Edited by Chris Murray. University of Dundee, February 2020. http://dx.doi.org/10.20933/100001152.

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Esposito, Stephen J. Analysis of Forensic Super Timelines. Fort Belvoir, VA: Defense Technical Information Center, June 2012. http://dx.doi.org/10.21236/ada562672.

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Chinn, Menzie, Barry Eichengreen, and Hiro Ito. A Forensic Analysis of Global Imbalances. Cambridge, MA: National Bureau of Economic Research, October 2011. http://dx.doi.org/10.3386/w17513.

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Velsko, S. Validation Strategies for Microbial Forensic Analysis. Office of Scientific and Technical Information (OSTI), August 2012. http://dx.doi.org/10.2172/1056616.

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David Baldwin, Max Morris, Stan Bajic, Zhigang Zhou, and James Kreiser. Statistical Tools for Forensic Analysis of Toolmarks. Office of Scientific and Technical Information (OSTI), April 2004. http://dx.doi.org/10.2172/825030.

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Reilly, Dallas D. Molecular Forensic Science Analysis of Nuclear Materials. Office of Scientific and Technical Information (OSTI), October 2012. http://dx.doi.org/10.2172/1053139.

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Borg, L., and I. Hutcheon. Forensic Analysis of samples from the Nuclear Fuel Cycle. Office of Scientific and Technical Information (OSTI), May 2013. http://dx.doi.org/10.2172/1080397.

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Chandramouli, Ramaswamy, Anoop Singhal, Duminda Wijesekera, and Changwei Liu. Methodology for enabling forensic analysis using hypervisor vulnerabilities data. Gaithersburg, MD: National Institute of Standards and Technology, June 2019. http://dx.doi.org/10.6028/nist.ir.8221.

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Hoeksema, Amy Beth. Statistical methods for the forensic analysis of striated tool marks. Office of Scientific and Technical Information (OSTI), January 2013. http://dx.doi.org/10.2172/1226173.

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Spotts, Ryan E. Objective forensic analysis of striated, quasi-striated and impressed toolmarks. Office of Scientific and Technical Information (OSTI), December 2014. http://dx.doi.org/10.2172/1227283.

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