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Connected Vehicle Forensics & Driver Attribution

Written by DFM Team


Connected Vehicle Forensics & Driver Attribution

A vehicle is now one of the most complex consumer items and with complexity comes opportunity. Criminals utilise them in most crimes, whether for personal transport and a projection of wealth, conveyance of contraband, drugs, firearms or people and financial crime. Vehicles have always been a prominent component in investigations. The UK homicide investigation manual specifically deals with vehicles as scenes and as a means to identify witnesses, locations, timelines, and association of individuals and in the civil court in terms of asset confiscation. However the digital footprint associated with vehicles has been overlooked by the investigation community due to the level of complexity or lack of awareness of what is actually available?

Vehicles have potentially useful persistent data retained on-board, data that can significantly assist with attribution and location evidence.

The connected vehicle whilst connected with a multitude of protocols is essentially another IoT device; a mobile phone, whether embedded or tethered, with wheels.

Jim Ogilvie explores the latest advancements in Vehicle Forensics.

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Coming up in the Next issue of Digital Forensics Magazine

Coming up in Issue 37 on sale from November 2018:


Crowd Sourcing Digital Evidence The Risk v The Reward

All digital devices used today can be considered as a potential source for digital evidence. Andrew Ryan investigates the current state in the art of crowd sourced digital evidence. Read More »

Recovery of Forensic Artifacts from Deleted Jump-List in Windows 10

Jump-Lists are widely discussed in forensics community since the release of Windows 7 and are having more capabilities to reveal forensics artifacts in Windows 10. Read More »

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Voice Biometrics

This article looks at the research and development in the field of Voice Biometrics and Speech Analytics, specifically Speaker Identification, Language and Gender Identification, Speech-to-Text Transcription, Keyword Spotting, and others. Read More »

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