Building a Use Case-Driven Adversarial Threat Matrix: A Comprehensive Approach
To effectively safeguard against increasingly so-phisticated and diverse cybersecurity threats, particularly those driven by Artificial Intelligence, a comprehensive understanding of the threat landscape is essential. A multifaceted threat matrix is introduced in this paper, developed within the KINAITI CS project and derived from the analysis of six diverse use cases and insights gathered from expert workshops. The matrix aims to highlight and prioritize emerging threats posed by AI -driven attacks and vulnerabilities.
Authors
- Antonis Voulgaridis (ORCID: https://orcid.org/0000-0003-4012-8511)
- Theodoros Semertzidis (ORCID: https://orcid.org/0000-0002-6825-4328)
- Efi Kafali
- Konstantinos Votis (ORCID: https://orcid.org/0000-0001-6381-8326)
- Georgios Rizos (ORCID: https://orcid.org/0009-0008-6470-5401)
- Petros Daras (ORCID: https://orcid.org/0000-0003-3814-6710)
- Stephane Gazut
- Prodromos Kiriakidis (ORCID: https://orcid.org/0009-0005-8336-8955)
Institutions
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
- Université Paris-Saclay (FR)
- Laboratoire d'Intégration des Systèmes et des Technologies (FR)
- Information Technologies Institute (GR)
- Centre for Research and Technology Hellas (GR)
Publication Details
- Published
- 2024-09-02
- DOI
- https://doi.org/10.1109/csr61664.2024.10679406
- Citations
- 1
- Primary Topic
- Advanced Malware Detection Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.35