Technical review examines cybersecurity vulnerabilities and mitigation strategies in artificial intelligence systems, highlighting the role of model interpretability in defense.
The integration of artificial intelligence (AI) into daily life and critical infrastructure has elevated the importance of addressing cybersecurity concerns within AI applications. While AI systems offer numerous benefits, such as enhanced efficiency, automation, and decision-making, they also introduce novel vulnerabilities and threats. Ensuring the security and reliability of these systems is crucial. This paper investigates key cybersecurity challenges associated with AI, including data privacy, integrity, adversarial attacks, and the ethical implications of AI in security. Additionally, it examines the role of Shapley Additive explainable AI in promoting transparency, allowing for greater interpretability of AI models and insights into decision-making processes.
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Bhuiyan et al. (2025) studied this question.
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