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

2025-04-25

AI Summary

Event reconstruction in digital forensics suffers from fragmented perspectives, inconsistent terminology, and methodological fragmentation, lacking a systematic, unifying framework. Method: This paper proposes the first unified temporal event reconstruction framework tailored for digital forensics—adapting classical forensic reconstruction models to the digital domain; constructing a comprehensive, lifecycle-spanning conceptual map of temporal reconstruction; and conducting a systematic literature review (SLR) coupled with conceptual modeling to clarify terminological relationships and process elements. Contribution/Results: The study identifies three core challenges—data scale, temporal distortion, and semantic ambiguity—and establishes an extensible classification system. It delivers a consensus-based terminology set and a standardized process paradigm, thereby providing a rigorous theoretical foundation for the development and evaluation of automated event reconstruction tools.

Technology Category

• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning
• Data Mining & Knowledge Management: Mining of Spatial, Temporal or Spatio-Temporal Data
• Cognitive Modeling & Cognitive Systems: Conceptual Inference and Reasoning

Application Category

• Security and Privacy: Cyber-crime defenses and forensics
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs
• Web Mining and Content Analysis: Models for Web evolution

Abstract

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.

Problem

• Lack of unified framework for timeline-based event reconstruction
• Fragmented research focusing narrowly on specific aspects
• Need for harmonized terminology and cohesive methodology

Innovation

• Proposes comprehensive timeline-based event reconstruction framework
• Harmonizes terminology and clarifies reconstruction process relationships
• Classifies challenges and suggests future research directions