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  1. ; ; ; (, Digital Forensics and Cyber Crime. ICDF2C 2021)
    Gladyshev, P.; Goel, S.; James, J.; Markowsky, G.; Johnson, D. (Ed.)
    AI Forensics is a novel research field that aims at providing techniques, mechanisms, processes, and protocols for an AI failure investigation. In this paper, we pave the way towards further exploring a sub-domain of AI forensics, namely AI model forensics, and introduce AI model ballistics as a subfield inspired by forensic ballistics. AI model forensics studies the forensic investigation process, including where available evidence can be collected, as it applies to AI models and systems. We elaborate on the background and nature of AI model development and deployment, and highlight the fact that these models can be replaced, trojanized, gradually poisoned, or fooled by adversarial input. The relationships and the dependencies of our newly proposed subdomain draws from past literature in software, cloud, and network forensics. Additionally, we share a use-case mini-study to explore the peculiarities of AI model forensics in an appropriate context. Blockchain is discussed as a possible solution for maintaining audit trails. Finally, the challenges of AI model forensics are discussed. 
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  2. ; ; ; (, Digital Forensics and Cyber Crime. ICDF2C 2021)
    Gladyshev, P.; Goel, S.; James, J.; Markowsky, G.; Johnson, D. (Ed.)
    Mobile device features like Apple CarPlay and Android Auto provide drivers safer hands-free navigation methods to use while driving. In crash investigations, understanding how these applications store data may be crucial in determining the what, when, where, who and why. By analyzing digital artifacts generated by Android Auto and Apple CarPlay, investigators can determine the last application displayed on the head unit, the application layout of the user’s home display screen, and other evidence which points to the utilization of the mobile device and its features while driving. Additionally, usage data can be found within other applications compatible with Android Auto and Apple CarPlay. In this paper, we explore the digital evidence produced by these applications and propose a proof of concept open source tool to assist investigators in automatically extracting relevant artifacts from Android Auto and Apple CarPlay as well as other day-to-day essential applications. 
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