AI-Driven Threat Detection: Enhancing Cloud Security with Generative Models for Real-Time Anomaly Detection and Risk Mitigation
Keywords:
Generative AI, Cloud Security, Anomaly Detection, Threat Intelligence, Cybersecurity, AI-driven Security, Risk Mitigation, Real-time Monitoring, Deep Learning, Adversarial AttacksAbstract
With the unsurpassed growth of cloud computing comes lots of security challenges that can be only solved by advanced threat detection solutions for safeguarding of sensible data and infrastructure. Traditional security system using rule-based intrusion detection and signature based threat monitoring can not prevent sophisticated cyber threats. As the generative AI models, VAEs, GANs, transformers and so on, they are also very powerful technology tools for real time anomaly detection & risk mitigation
References
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M. Brown et al., “Generative AI Models for Intrusion Detection in Cloud Networks,” Journal of Cloud Security, vol. 11, no. 4, pp. 223–239, Oct. 2022.
R. Zhang and T. Li, “AI-Powered Threat Intelligence in Cloud Computing,” IEEE Internet of Things Journal, vol. 10, no. 2, pp. 678–690, Feb. 2021.
