Robustness and Security in AI Systems: Challenges and Solutions

Main Article Content

Professor Alexander Lee

Abstract

Ensuring the robustness and security of artificial intelligence (AI) systems is paramount to their safe and reliable deployment across various domains. This paper investigates the challenges posed by adversarial attacks, data poisoning, and system vulnerabilities in AI applications and proposes solutions to enhance the resilience of AI systems against such threats. Through a comprehensive analysis of defense mechanisms such as adversarial training, robust optimization, and model verification techniques, this paper aims to provide a roadmap for building more secure and trustworthy AI systems capable of withstanding malicious manipulations and ensuring user safety and privacy.

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How to Cite
Robustness and Security in AI Systems: Challenges and Solutions. (2024). International Meridian Journal, 6(6). https://meridianjournal.in/index.php/IMJ/article/view/52
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Articles

How to Cite

Robustness and Security in AI Systems: Challenges and Solutions. (2024). International Meridian Journal, 6(6). https://meridianjournal.in/index.php/IMJ/article/view/52

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