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20222024
most citedAttacks, Defenses, And Tools: A Framework To Facilitate Robust AI/ML Systems

4 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2024

Establishing Minimum Elements for Effective Vulnerability Management in AI Software

Mohamad Fazelnia, Sara Moshtari, Mehdi Mirakhorli

In the rapidly evolving field of artificial intelligence (AI), the identification, documentation, and mitigation of vulnerabilities are paramount to ensuring robust and secure syst…

cs.SE2024

Lessons from the Use of Natural Language Inference (NLI) in Requirements Engineering Tasks

Mohamad Fazelnia, Viktoria Koscinski, Spencer Herzog +1

We investigate the use of Natural Language Inference (NLI) in automating requirements engineering tasks. In particular, we focus on three tasks: requirements classification, identi…

cs.SE2023

A Novel Approach to Identify Security Controls in Source Code

Ahmet Okutan, Ali Shokri, Viktoria Koscinski +2

Secure by Design has become the mainstream development approach ensuring that software systems are not vulnerable to cyberattacks. Architectural security controls need to be carefu…

cs.CR2022

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

Mohamad Fazelnia, Ahmet Okutan, Mehdi Mirakhorli

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 Adversa…

cs.CR2022★ 4 cited

Attacks, Defenses, And Tools: A Framework To Facilitate Robust AI/ML Systems

Mohamad Fazelnia, Igor Khokhlov, Mehdi Mirakhorli

Software systems are increasingly relying on Artificial Intelligence (AI) and Machine Learning (ML) components. The emerging popularity of AI techniques in various application doma…