Supporting AI/ML Security Workers through an Adversarial Techniques, Tools, and Common Knowledge (AI/ML ATT&CK) Framework

Autor:	Fazelnia, Mohamad, Okutan, Ahmet, Mirakhorli, Mehdi
Rok vydání:	2022
Předmět:	Computer Science - Cryptography and Security
Druh dokumentu:	Working Paper
Popis:	This paper focuses on supporting AI/ML Security Workers -- professionals involved in the development and deployment of secure AI-enabled software systems. It presents AI/ML Adversarial Techniques, Tools, and Common Knowledge (AI/ML ATT&CK) framework to enable AI/ML Security Workers intuitively to explore offensive and defensive tactics. Comment: AI/ML ATT&CK
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2211.05075 Zobrazit plný text záznamu View this record from Arxiv