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Chris Hargreaves

Publications and source records attributed to Chris Hargreaves.

4 recordsLinked to original sources

SoK: Understanding Anti-Forensics Concepts and Research Practices Across Forensic Subdomains

Anti-forensics includes a growing set of techniques designed to obstruct forensic analysis. While cybercriminals increasingly rely on these methods, they also help researchers identify and remedy weaknesses in forensic tools, advancing the overall robustness of digital forensics. Despite repeated efforts to define it, anti-forensics remains vague and inconsistent in its use. It also poses ethical challenges regarding the appropriateness of research practices and the legitimacy of the field itself. This article presents a systematic analysis of 123 publications on anti-forensics, combining qualitative and quantitative methods. We quantify the main techniques and attack vectors, examine their occurrence in different digital forensic subdomains, and identify typical research methods, motivations, and applications. This work also discusses what these findings mean for future research and proposes directions for building a more coherent and ethically grounded understanding of anti-forensics.

cs.CR

SoK: Timeline based event reconstruction for digital forensics: Terminology, methodology, and current challenges

Event reconstruction is a technique that examiners can use to attempt to infer past activities by analyzing digital artifacts. Despite its significance, the field suffers from fragmented research, with studies often focusing narrowly on aspects like timeline creation or tampering detection. This paper addresses the lack of a unified perspective by proposing a comprehensive framework for timeline-based event reconstruction, adapted from traditional forensic science models. We begin by harmonizing existing terminology and presenting a cohesive diagram that clarifies the relationships between key elements of the reconstruction process. Through a comprehensive literature survey, we classify and organize the main challenges, extending the discussion beyond common issues like data volume. Lastly, we highlight recent advancements and propose directions for future research, including specific research gaps. By providing a structured approach, key findings, and a clearer understanding of the underlying challenges, this work aims to strengthen the foundation of digital forensics.

cs.CR

Evaluating tamper resistance of digital forensic artifacts during event reconstruction

Event reconstruction is a fundamental part of the digital forensic process, helping to answer key questions like who, what, when, and how. A common way of accomplishing that is to use tools to create timelines, which are then analyzed. However, various challenges exist, such as large volumes of data or contamination. While prior research has focused on simplifying timelines, less attention has been given to tampering, i.e., the deliberate manipulation of evidence, which can lead to errors in interpretation. This article addresses the issue by proposing a framework to assess the tamper resistance of data sources used in event reconstruction. We discuss factors affecting data resilience, introduce a scoring system for evaluation, and illustrate its application with case studies. This work aims to improve the reliability of forensic event reconstruction by considering tamper resistance.

cs.CR

SoK: Exploring the State of the Art and the Future Potential of Artificial Intelligence in Digital Forensic Investigation

Multi-year digital forensic backlogs have become commonplace in law enforcement agencies throughout the globe. Digital forensic investigators are overloaded with the volume of cases requiring their expertise compounded by the volume of data to be processed. Artificial intelligence is often seen as the solution to many big data problems. This paper summarises existing artificial intelligence based tools and approaches in digital forensics. Automated evidence processing leveraging artificial intelligence based techniques shows great promise in expediting the digital forensic analysis process while increasing case processing capacities. For each application of artificial intelligence highlighted, a number of current challenges and future potential impact is discussed.

cs.CR