Overview
This study presents a structured synthesis of digital vehicle forensics (DVF), addressing its less mature state compared to other forensic disciplines. It defines DVF, formalizes its triage problem, and outlines eight core characteristics derived from academic literature and case material. The research provides a conceptual framework intended for understanding, planning, and communicating DVF investigations, rather than an algorithmic performance claim.
Research Context
Modern vehicles are characterized as cyber-physical, networked systems that may contain digital traces relevant to a range of investigations. These investigations can include accident reconstruction, crime investigation, warranty analysis, and cybersecurity incident response. However, the field of DVF is described as being less mature than established areas such as computer, mobile, and cloud forensics. This relative immaturity is attributed to the distribution of relevant data across multiple sources, including in-vehicle components, mobile devices, manufacturer back ends, third-party services, and physical evidence.
Approach
The research methodology involved a structured synthesis of academic literature, relevant standards, and practitioner-oriented sources. This synthesis aimed to address the identified gap in the maturity of DVF. The process began by defining DVF and subsequently formalizing the challenges associated with it. From this analysis, characteristics of DVF were derived and an adversarial perspective was incorporated. Finally, a characteristic-driven triage procedure was developed.
Findings
Definition of Digital Vehicle Forensics (DVF)
The study defines DVF as encompassing the identification, preservation, acquisition, verification, interpretation, and reporting of vehicle-related digital evidence. These activities must adhere to specific constraints: safety, legal requirements, privacy considerations, and forensic-soundness principles.
Formalization of the DVF Triage Problem
The DVF triage problem is formalized as the process of selecting and correlating evidence sources. This selection and correlation are subject to several constraints: volatility of data, accessibility of sources, safety implications, data integrity, and authorization requirements.
Eight Characteristics of Digital Vehicle Forensics
Eight specific characteristics were derived from the synthesized literature and case material. These characteristics are:
- Multiple users: Implies various individuals interacting with the vehicle and its systems.
- Massively networked: Refers to the extensive interconnectedness of components within the vehicle and to external systems.
- Cyber-physical system: Highlights the integration of computational and physical processes.
- Dependencies between components: Indicates that the functionality and data integrity of one component often rely on others.
- Functional data: Relates to data generated by the operational functions of the vehicle.
- Safety implications: Acknowledges the potential for forensic activities to impact vehicle safety or human well-being.
- Accessibility: Addresses the ease or difficulty in reaching and extracting data from various sources.
- Limited abstraction: Suggests that raw data may require detailed interpretation due to a lack of high-level functional views.
Adversarial Perspective and Triage Procedure
The research incorporates an adversarial perspective and proposes a characteristic-driven triage procedure. This procedure is designed to assist investigators in prioritizing evidence sources. Concurrently, it emphasizes the documentation of assumptions made, limitations encountered, and potential failure cases during an investigation. The resulting contribution is presented as a reproducible conceptual framework for DVF investigations.
Why This Matters
This work offers a structured framework to improve understanding, planning, and communication in digital vehicle forensic investigations. By defining DVF and its challenges, and outlining specific characteristics, it provides a foundational basis for addressing the complexities of digital evidence within modern vehicles.