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Computer Science > Cryptography and Security

arXiv:2401.07960 (cs)
[Submitted on 15 Jan 2024]

Title:ADMIn: Attacks on Dataset, Model and Input. A Threat Model for AI Based Software

Authors:Vimal Kumar, Juliette Mayo, Khadija Bahiss
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Abstract:Machine learning (ML) and artificial intelligence (AI) techniques have now become commonplace in software products and services. When threat modelling a system, it is therefore important that we consider threats unique to ML and AI techniques, in addition to threats to our software. In this paper, we present a threat model that can be used to systematically uncover threats to AI based software. The threat model consists of two main parts, a model of the software development process for AI based software and an attack taxonomy that has been developed using attacks found in adversarial AI research. We apply the threat model to two real life AI based software and discuss the process and the threats found.
Subjects: Cryptography and Security (cs.CR)
ACM classes: K.6.5
Cite as: arXiv:2401.07960 [cs.CR]
  (or arXiv:2401.07960v1 [cs.CR] for this version)
  https://doi.org/10.48550/arXiv.2401.07960

Submission history

From: Vimal Kumar [view email]
[v1] Mon, 15 Jan 2024 20:55:21 UTC (897 KB)
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