Integrating Artificial Intelligence into Cloud Security: Future Trends, Privacy Challenges, and Mitigation Strategies
Keywords:
cloud security; artificial intelligence; machine learning; privacy; differential privacy; federated learning; threat detectionAbstract
Cloud computing now underpins the majority of enterprise workloads, yet its shared, elastic,and multi-tenant nature widens the attack surface faster than traditional, rule-based controlscan adapt. Artificial intelligence (AI)—particularly machine learning (ML) and deep
learning—has emerged as a means of detecting novel threats, automating response, and reasoning over the vast telemetry that cloud environments generate
References
1. Abadi, M., Chu, A., Goodfellow, I., McMahan, H.B., Mironov, I., Talwar, K. & Zhang, L. (2016) 'Deep learning with differential privacy', Proceedings of the ACM SIGSAC Conference on Computer and Communications Security (CCS), pp. 308–318. Available at: https://doi.org/10.1145/2976749.2978318
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Published
2023-05-20
How to Cite
Viral Dhirenkumar Pala. (2023). Integrating Artificial Intelligence into Cloud Security: Future Trends, Privacy Challenges, and Mitigation Strategies . Journal of Computational Analysis and Applications (JoCAAA), 31(4), 3227–3238. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5835
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