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: 15 June 2025

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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 (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 (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 (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 (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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Haoyang, Xie, Jiang Keyu, Yuan Xiaohong, and Zeng Hongbiao. "FORENSIC ANALYSIS OF WINDOWS REGISTRY AGAINST INTRUSION." FORENSIC ANALYSIS OF WINDOWS REGISTRY AGAINST INTRUSION 4, no. 2 (2012): 121–34. https://doi.org/10.5281/zenodo.3247268.

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Windows Registry forensics is an important branch of computer and network forensics. Windows Registry is often considered as the heart of Windows Operating Systems because it contains all of the configuration setting of specific users, groups, hardware, software, and networks. Therefore, Windows Registry can be viewed as a gold mine of forensic evidences which could be used in courts. This paper introduces the basics of Windows Registry, describes its structure and its keys and subkeys that have forensic values. This paper also discusses how the Windows Registry forensic keys can be applied in intrusion detection.
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Al Jouhi, Mariam, and Sara Al Hosani. "Windows Forensics Analysis." Emirati Journal of Policing & Security Studies 1, no. 1 (2022): 4–11. https://doi.org/10.54878/jagh3855.

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Computer forensics investigates crimes on digital devices hard disk and any other digital storage devices to determine the evidence of any unauthorized access. Essentially, forensic investigators conduct forensic analysis with the help of different approaches (Static and Dynamic) and also tools like ProDiscover, Encase, Accessdata FTK and Autopsy to guarantee the security of a system in an organization. The process requires knowledge of different registry, laws, and regulations related to computer crimes, the operating system (Windows, Linux, etc.) and the network in an organization (e.g., Win NT). In this paper we will use different forensic tools to extract forensic evidence from a windows environment.
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Maulina, Sinta Nur, Niken Dwi Wahyu Cahyani, and Erwid Musthofa Jadied. "ANALYSIS OF THE EFFECT OF VSM ON THE MEMORY ACQUISITION PROCESS USING THE DYNAMIC ANALYSIS METHOD." JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) 8, no. 2 (2023): 638–46. http://dx.doi.org/10.29100/jipi.v8i2.3745.

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At first, forensics was restricted to studying data that was stored on a system's hard disk. However, as storage capacity and data encryption increased, applying conventional digital forensic procedures became more challenging. As a result, memory forensics techniques are developed, or are frequently referred to as live forensics, because the process is quicker and more sophisticated. Volatile memory forensics, often known as live forensics, are necessary for this condition. Live forensics has flaws, specifically that some programs can fail when the computer is in active VSM (virtual secure mode). This results in the retrievable evidence being lost. Therefore, determining the cause is essential. The software-based memory acquisition tools Autopsy, Isobuster, DumpIt, and Magnet RAM Capturer are just a few examples. According to the findings of the experiments, the tools that have crashed include DumpIt v1.3.2.20110401. A dynamic code analysis using WindBg as a tool was utilized to study the impact of VSM on the memory acquisition tool. This study's goal is to identify the instances of crashes in various forensic instruments, which will be highly useful for forensic experts performing investigations.
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Lee, Sang Young. "Mobile Digital Forensics Framework for Smartphone User Analysis." Webology 19, no. 1 (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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Dwi Syahputri, Rischi, Alexander Anggono, Prasetyono Prasetyono, and Mohamad Djasuli. "Evolution and Research Opportunities of Digital Forensic Tools: A Bibliometric Analysis." CogITo Smart Journal 10, no. 2 (2024): 474–85. https://doi.org/10.31154/cogito.v10i2.675.474-485.

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The use of digital technology has increased rapidly, presenting new challenges such as cybercrime, online fraud and money laundering. To address these threats, digital forensic tools have become crucial in investigating and analyzing electronic evidence to combat increasingly complex digital crimes. Therefore, research and development in the field of digital forensics is crucial to address the growing digital security challenges. This study aims to conduct a bibliometric analysis of digital forensic tools research in the business, management and accounting domains over the past ten years, evaluate the evolution of the research, identify promising research opportunities and provide insights into future directions in the field. Bibliometric analysis was conducted with the help of VOSviewer software on 698 Scopus-indexed articles sourced from ScienceDirect during 2014-2023. Based on the network map analysis, it was found that despite much progress, the field continues to evolve and offers many opportunities for further research and innovation in digital forensic tools related to mobile forensics, memory forensics, anti-forensics, malware analysis, cloud forensics, cybersecurity, machine learning and deep learning, and ethics and privacy in forensic investigations.
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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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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.<br>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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Cembalo, Maurizio. "Forensic analysis for digital images." Doctoral thesis, Universita degli studi di Salerno, 2011. http://hdl.handle.net/10556/227.

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IX n.s.<br>Nowadays, taking and sharing digital pictures is becoming a very popular activity. This is witnessed by the explosive growth of the digital cameras market: e.g., more than one billion of digital cameras have been produced and shipped in 2010. A consequence of this trend is that also the number of crimes involving digital pictures increases, either because pictures are part of the crime (e.g., exchanging pedopornographic pictures) or because their analysis may reveal some important clue about the author of the crime. The highly technical nature of computer crimes facilitated a wholly new branch of forensic science called digital forensics. The Digital Forensic Sci- ence involves processes such as acquisition of data from an electronic source, analysis of the acquired data, extraction of evidence from the data, and the preservation and presentation of the evidence. Digital Imaging Forensics is a specialization of the Digital Forensics which deals with digital images. One of the many issues that the Digital Imaging Forensics tries to deal with is the source camera identi cation problem, i.e., establish if a given image has been taken by a given digital camera. Today this is a practical and important problem aiming to identify reliably the imaging device that acquired a particular digital image. Techniques to authenticate an electronic image are especially important in court. For example, identifying the source device could establish the origin of images presented as evidence. In a prosecution for child pornography, for example, it could be desirable that one could prove that certain imagery was obtained with a speci c camera and is thus not an image generated by a computer, given that "virutal images" are not considered offense. As electronic images and digital video replace their analog counterparts, the importance of reliable, inexpensive, and fast identification of the origin of a particular image will increase. The identification of a source camera of an image is a complex issue which requires the understanding of the several steps involved in the creation of the digital photographic representation of a real scene. In particular, it is necessary to understand how the digital images are created, which are the processes which create (and therefore affect) the creation of the digital data, starting from the real scene. Moreover, it is necessary to point out the factors which can be used to support the camera identification and, may be even more important, which are the factors which can tamper the photos and prevent (maliciously or not) the camera identification. Many identification techniques have been proposed so far in literature. All these techniques generally work by using the sensor noise (an unexpected variation of the digital signal) left by a digital sensor when taking a picture as a fingerprint for identifying the sensor. These studies are generally accompanied with tests proving the effectiveness of these techniques, both in terms of False Acceptance Rate (FAR) and False Rejection Rate (FRR). Unfortunately, most of these contributions do not take into consideration that, in practice, the images that are shared and exchanged over the Internet have often been pre-processed. Instead, it is a common practice to assume that the images to be examined are unmodified or, at most, to ignore the e ects of the pre-processing. Even without considering the case of malicious users that could intention- ally process a picture in order to fool the existing identification techniques, this assumption is unrealistic for at least two reasons. The first is that, as previously mentioned, almost all current photo-managing software o ers several functions for adjusting, sometimes in a "magic" way (see the "I'm feeling lucky" function on Google Picasa) different characteristics of a picture. The second reason can be found in the way the images are managed by some of the most important online social network (OSN) and online photo sharing (OPS) sites. These services usually make several modifications to the original photos before publishing them in order to either improve their appearance or reduce their size. In this thesis we have first implemented the most prominent source camera identification technique, proposed by Lukas et al. and based on the Photo-Response Non-Uniformity. Then, we present a new identification technique that use a SVM (Support Vector Macchine) classifier to associate photos to the right camera. Both our implementation of Lukas et al. technique and our SVM technique have been extensively tested on a test-sample of nearly 2500 images taken from 8 different cameras. The main purpose of the experiments conducted is to see how these techniques performs in presence of pre-processed images, either explicit modified by a user with photo management tools or modified by OSNs and OPSs services without user awareness. The results confirm that, in several cases, the method by Lukas et al. and our SVM technique is resilient to the modifications introduced by the considered image-processing functions. However, in the experiments it has been possible to identify several cases where the quality of the identifica- tion process was deteriorated because of the noise introduced by the image- processing. In addition, when dealing with Online Social Networks and Online Photo Sharing services, it has been noted that some of them process and modify the uploaded pictures. These modifications make ineffective, in many cases, the method by Lukas et al. while SVM technique performs slightly better. [edited by author]<br>2009 - 2010
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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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<p> 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.</p>
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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.<br>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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<p>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.</p>
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Books on the topic "Forensic analysis"

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Cupples Connon, Catherine, ed. Forensic DNA Analysis. Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-3295-6.

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

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Group, Search, ed. Forensic DNA analysis: Issues. U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Statistics, 1991.

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

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K, Bhasin M., Surinder Nath, and Sehgal V. N, eds. Human blood analysis. Kamla-Raj Enterprises, 2007.

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

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

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Allen, Michael. Foundations of Forensic Document Analysis. John Wiley & Sons, Ltd, 2015. http://dx.doi.org/10.1002/9781118729922.

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Zadora, Grzegorz, Agnieszka Martyna, Daniel Ramos, and Colin Aitken. Statistical Analysis in Forensic Science. John Wiley & Sons Ltd, 2013. http://dx.doi.org/10.1002/9781118763155.

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Maher, Robert C. Principles of Forensic Audio Analysis. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99453-6.

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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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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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Du, Suwen, Pengpeng Yang, Daniele Baracchi, Jinglian Jin, Dasara Shullani, and Alessandro Piva. "ForensiCam-215K: A Large Scale Image and Video Dataset for Forensic Analysis." In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2025. https://doi.org/10.1109/icassp49660.2025.10890764.

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Dragonas, Evangelos, and Costas Lambrinoudakis. "Forensic Analysis of Android Notifications' History." In 2024 IEEE International Conference on Cyber Security and Resilience (CSR). IEEE, 2024. http://dx.doi.org/10.1109/csr61664.2024.10679344.

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Xi, Jian, Lukas Jaeckel, Michael Spranger, Melanie Siegel, and Dirk Labudde. "Forensic Communication Analysis: Challenges and Opportunities." In 2024 IEEE International Conference on Cyber Security and Resilience (CSR). IEEE, 2024. http://dx.doi.org/10.1109/csr61664.2024.10679503.

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Monkam, Galamo F., and Nathaniel D. Bastian. "Model Poisoning Detection via Forensic Analysis." In MILCOM 2024 - 2024 IEEE Military Communications Conference (MILCOM). IEEE, 2024. https://doi.org/10.1109/milcom61039.2024.10774017.

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Lolla, Tapasvi, Wayne Li, Laurie Burnham, and Bruce King. "Forensic Analysis of Failed Photovoltaic Connectors." In 2024 IEEE 52nd Photovoltaic Specialist Conference (PVSC). IEEE, 2024. http://dx.doi.org/10.1109/pvsc57443.2024.10748973.

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Rahman, Rizwan Ur, Abanteeka Acharya, Sanjipan Deb, and Priyanshi Panchal. "Dynamic Forensic Analysis of CryptBot Malware." In 2025 IEEE 14th International Conference on Communication Systems and Network Technologies (CSNT). IEEE, 2025. https://doi.org/10.1109/csnt64827.2025.10967635.

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Rodrigues, Anisha P., Pratham S. Shetty, Preethika Shet, et al. "Deep Learning in Forensic Sketch Analysis." In 2025 International Conference on Artificial Intelligence and Data Engineering (AIDE). IEEE, 2025. https://doi.org/10.1109/aide64228.2025.10987486.

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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. 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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Reports on the topic "Forensic analysis"

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Fernández Corcobado, Isabel, Alejandro Maestre Gasteazi, and Unai Tapia. Forensic Analysis of Images. Florida International University, 2024. https://doi.org/10.25148/gfjcsr.2024.2.

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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, 2020. http://dx.doi.org/10.20933/100001152.

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Esposito, Stephen J. Analysis of Forensic Super Timelines. Defense Technical Information Center, 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. National Bureau of Economic Research, 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), 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), 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), 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), 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. National Institute of Standards and Technology, 2019. http://dx.doi.org/10.6028/nist.ir.8221.

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Sauerwein, Kelly. Bitemark Analysis Reference List. National Institute of Standards and Technology, 2022. http://dx.doi.org/10.6028/nist.ir.8352sup4.

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Abstract:
This report provides supplemental information to NISTIR 8352 Bitemark Analysis: A NIST Scientific Foundation Review. Publicly available resources relating to bitemark analysis were collected to assist in the review of the scientific foundations of bitemark analysis conducted by the National Institute of Standards and Technology (NIST). Over 400 sources were collected from literature searches and input from previous efforts by the National Institute of Justice Forensic Technology Center of Excellence, the American Board of Forensic Odontology (ABFO), and other public resources. This reference list is meant as a resource for the odontology community and interested stakeholders but does not represent an exhaustive compilation of the literature pertaining to bitemark analysis.
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