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

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autores principales: Kumar, Vimal, Mayo, Juliette, Bahiss, Khadija
Formato: Preprint
Publicado: 2024
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866911758490271744
author Kumar, Vimal
Mayo, Juliette
Bahiss, Khadija
author_facet Kumar, Vimal
Mayo, Juliette
Bahiss, Khadija
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2401_07960
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle ADMIn: Attacks on Dataset, Model and Input. A Threat Model for AI Based Software
Kumar, Vimal
Mayo, Juliette
Bahiss, Khadija
Cryptography and Security
K.6.5
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.
title ADMIn: Attacks on Dataset, Model and Input. A Threat Model for AI Based Software
topic Cryptography and Security
K.6.5
url https://arxiv.org/abs/2401.07960