A generalized approach to automotive forensics

Buquerin, Kevin Klaus Gomez; Corbett, Christopher; Hof, Hans-Joachim

doi:10.1016/j.fsidi.2021.301111

Cited by 12 publications

(9 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In contrast, data Example of data and source External devices. [24]- [26], [31], [32], [36], [63], [65], [68]- [70], [73], [74], [77], [81], [82], [112] C.I.A.N.P. LE.VM.VD.…”

Section: Discussionmentioning

confidence: 99%

“…We have chosen the four most common data users referred to in the literature [18], [19], [24]- [26].…”

Section: Stakeholdersmentioning

confidence: 99%

“…In [26], K. Buquerin et al presents a potential automotive digital forensic process according to four phases: forensic readiness, data acquisition, data analysis, and documentation. The OBD-II port was used as an example for a connection point for data collection with Wireshark.…”

Section: B Categorization Of Papersmentioning

confidence: 99%

See 2 more Smart Citations

A Systematic Literature Review on Automotive Digital Forensics: Challenges, Technical Solutions and Data Collection

Strandberg

Nowdehi

Olovsson

2023

IEEE Trans. Intell. Veh.

View full text Add to dashboard Cite

A modern vehicle has a complex internal architecture and is wirelessly connected to the Internet, other vehicles, and the infrastructure. The risk of cyber attacks and other criminal incidents along with recent road accidents caused by autonomous vehicles calls for more research on automotive digital forensics. Failures in automated driving functions can be caused by hardware and software failures and cyber security issues. Thus, it is imperative to be able to determine and investigate the cause of these failures, something which requires trustable data. However, automotive digital forensics is a relatively new field for the automotive where most existing self-monitoring and diagnostic systems in vehicles only monitor safety-related events. To the best of our knowledge, our work is the first systematic literature review on the current research within this field. We identify and assess over 300 papers published between 2006 -2021 and further map the relevant papers to different categories based on identified focus areas to give a comprehensive overview of the forensics field and the related research activities. Moreover, we identify forensically relevant data from the literature, link the data to categories, and further map them to required security properties and potential stakeholders. Our categorization makes it easy for practitioners and researchers to quickly find relevant work within a particular sub-field of digital forensics. We believe our contributions can guide digital forensic investigations in automotive and similar areas, such as cyber-physical systems and smart cities, facilitate further research, and serve as a guideline for engineers implementing forensics mechanisms.

show abstract

“…In contrast, data Example of data and source External devices. [24]- [26], [31], [32], [36], [63], [65], [68]- [70], [73], [74], [77], [81], [82], [112] C.I.A.N.P. LE.VM.VD.…”

Section: Discussionmentioning

confidence: 99%

“…We have chosen the four most common data users referred to in the literature [18], [19], [24]- [26].…”

Section: Stakeholdersmentioning

confidence: 99%

See 1 more Smart Citation

A Systematic Literature Review on Automotive Digital Forensics: Challenges, Technical Solutions and Data Collection

Strandberg

Nowdehi

Olovsson

2023

IEEE Trans. Intell. Veh.

View full text Add to dashboard Cite

show abstract

“…41 Bates 2019; Salvation Data 2021. 42 Gomez Buquerin et al 2021;Forensics Colleges 2022;Répás et al 2022;Parkinson 2022. 43 Interpol 2021Répás et al 2022;Interpol 2022. of the content and methodology of the term automotive forensics, the possibilities provided by the information available in the study justify the definition of a new concept.…”

Section: Digital Vehicle -Automotive Forensicsmentioning

confidence: 99%

Definition of Forensic Methodologies for Autonomous Vehicles

Répás¹

2023

View full text Add to dashboard Cite

Digitisation is present more and more widely in the vehicle industry, the use of modern and increasingly self-driving vehicles is appearing more and more widely. Their use becomes more appropriate and necessary in industry, transport, military and logistics applications. The spread of these highly automated vehicles will have a direct impact on road accidents, violations and crimes. In the event of accidents, the determination of responsibility and the identification of the perpetrators of crimes will continue to be necessary in the future, for which tools and procedures are currently not available or not fully applicable. By connecting vehicles and infrastructure elements, the range of data related to events has been greatly enhanced. This information must be extracted and analysed during the investigations. The purpose of the investigations is to determine what, when, where and how it happened, who were involved, and to determine responsibility. The basis of the expert investigation of self-driving vehicles and cooperative transport systems is the classical forensic procedure and digital forensics. On the other hand, the field requires specific knowledge, preparation, specific tools and approach. In this study, the existing, already used digital forensics examination methods are described,the applicability of some of them, some steps or tools that require further examination in the case of modern and increasingly autonomous vehicles.

show abstract

“…Bequerin et al [18] proposed the four-phase forensic process for vehicles. The process consists of forensic readiness, data acquisition, data analysis, and documentation.…”

Section: Related Workmentioning

confidence: 99%

Android-Based Audio Video Navigation System Forensics: A Case Study

et al. 2023

View full text Add to dashboard Cite

Vehicle digital forensics includes the process of collecting and analysing digital data stored in vehicles to find evidence related to traffic accidents or crime scenes. Through this process, we can reconstruct digital events by recognizing various information such as driver behaviour, driving patterns, vehicle destinations, and smartphones connected to a vehicle. Recently, many vehicle digital forensic studies have been conducted, but few of them have dealt with Android-based infotainment (or audio video navigation, AVN) systems. While many AVN systems adopt Android as the operating system, digital forensics of Android-based AVN systems is not easy. This is because Android-based AVN systems support various storage devices and data formats and have various data sources, making consistent data collection or analysis difficult. In this article, we perform digital forensics on four AVN systems: two Android 4.2.2 Jellybean-based and two Android 4.4.2 KitKat-based, aiming to develop a data acquisition and analysis method appropriate for each Android version. As a data collection method for the AVN system forensics, logical data acquisition is performed on the Jellybean-based systems and physical data acquisition on the KitKat-based systems. For the collected data, we identify and analyse Bluetooth data, navigation data, and system logs individually. Next, we investigate the differences in the storage structure and file location of major digital artefacts depending on the Android versions and show the limitations of the individual data analysis. Finally, we construct a timeline for the driver’s activities by integrating and analysing the diverse artefacts which consist of Bluetooth data, navigation data, and system logs.

show abstract

A generalized approach to automotive forensics

Cited by 12 publications

References 6 publications

A Systematic Literature Review on Automotive Digital Forensics: Challenges, Technical Solutions and Data Collection

A Systematic Literature Review on Automotive Digital Forensics: Challenges, Technical Solutions and Data Collection

Definition of Forensic Methodologies for Autonomous Vehicles

Android-Based Audio Video Navigation System Forensics: A Case Study

Contact Info

Product

Resources

About