Artificial intelligence is transforming cybersecurity and data protection, enabling automated threat detection, intelligent incident response, and proactive vulnerability identification that were previously impossible with rule-based systems alone. iously impossible with rule-based systems alone. This paper presents a comprehensive analysis of AI-driven approaches to cybersecurity and data protection, examining both the opportunities and challenges that AI introduces to the security landscape. We analyze the dual-use nature of AI in security contexts, where the same techniques that enable advanced threat detection can also be weaponized by a dversaries to launch more sophisticated attacks. The paper reviews state-of-the-art AI security techniques across threat detection, malware analysis, vulnerability assessment, and privacy protection domains. We identify key challenges including adversarial attacks on AI models, data quality issues, interpretability requirements, and the evolving regulatory landscape. Based on our analysis, we propose a framework for responsible AI deployment in security applications.
Mohamed Safa (Mon,) studied this question.
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