Proceedings of the 8th International Conference on Teaching, Learning and Education
Year: 2024
DOI:
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Securing the Intelligent Future: Mitigating Attacks in AI
Nidhi Joshi Parsai, Rashmi Vijaywargiya, Sumit Jain
ABSTRACT:
Artificial intelligence (AI) deployments become more prevalent across industries, the need for robust security measures to protect against attacks becomes paramount. This paper explores the various attack vectors that target AI systems and proposes effective strategies for mitigating these threats. We examine adversarial attacks, data poisoning, model inversion attacks, and backdoor attacks, highlighting their potential impact on critical applications such as autonomous vehicles, medical diagnosis, and financial fraud detection. To fortify AI systems, we delve into state-of-the-art defence mechanisms, including robust training techniques, anomaly detection, adversarial training, and secure model deployment practices. We also discuss the challenges and limitations associated with implementing these defences and provide insights into future research directions. By prioritizing security measures, we can ensure the responsible and secure integration of AI technologies, safeguarding the intelligent future.
keywords: Securing, Intelligent Future Mitigating Attacks, AI Deployments