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

Vimal Kumar; Juliette Mayo; Khadija Bahiss

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arXiv · 2401.07960

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

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.

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BibTeX RIS

Vimal Kumar, Juliette Mayo, Khadija Bahiss. 2024-01-15. ADMIn: Attacks on Dataset, Model and Input. A Threat Model for AI Based Software. https://arxiv.org/abs/2401.07960

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