[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Vimal Kumar ; Juliette Mayo and Khadija Bahiss

Affiliation: School of Computing and Mathematical Sciences, University of Waikato, Hamilton, New Zealand

Keyword(s): Threat Modelling, Artificial Intelligence, Machine Learning, Taxonomy.

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 79.170.44.78

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Kumar, V. ; Mayo, J. and Bahiss, K. (2024). ADMIn: Attacks on Dataset, Model and Input: A Threat Model for AI Based Software. In Proceedings of the 10th International Conference on Information Systems Security and Privacy - ICISSP; ISBN 978-989-758-683-5; ISSN 2184-4356, SciTePress, pages 170-178. DOI: 10.5220/0012394100003648

@conference{icissp24,
author={Vimal Kumar and Juliette Mayo and Khadija Bahiss},
title={ADMIn: Attacks on Dataset, Model and Input: A Threat Model for AI Based Software},
booktitle={Proceedings of the 10th International Conference on Information Systems Security and Privacy - ICISSP},
year={2024},
pages={170-178},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012394100003648},
isbn={978-989-758-683-5},
issn={2184-4356},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Information Systems Security and Privacy - ICISSP
TI - ADMIn: Attacks on Dataset, Model and Input: A Threat Model for AI Based Software
SN - 978-989-758-683-5
IS - 2184-4356
AU - Kumar, V.
AU - Mayo, J.
AU - Bahiss, K.
PY - 2024
SP - 170
EP - 178
DO - 10.5220/0012394100003648
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic

<style> #socialicons>a span { top: 0px; left: -100%; -webkit-transition: all 0.3s ease; -moz-transition: all 0.3s ease-in-out; -o-transition: all 0.3s ease-in-out; -ms-transition: all 0.3s ease-in-out; transition: all 0.3s ease-in-out;} #socialicons>ahover div{left: 0px;} </style>