Cloud plays a pivotal role in the ever-growing world of technology. A significant amount of data and computing equipment is hosted on the cloud. This helps in achieving the highest levels of service excellence and redundancy. However, this also makes the cloud a target of cyber-attacks. Cybersecurity in cloud environment is of paramount importance due to the dynamic and interconnected nature of cloud services. Cloud has an increased attack surface and coupled with the rapid deployment and decommissioning of resources there is a need for continuous monitoring in order to detect and respond to security incidents promptly. This paper uses a nature-based optimizer in Manta Ray Foraging Optimization with different classical Machine Learning classifiers in order to detect cloud based cyber-attacks. The performance of the ML models is the compared and an optimal solution is proposed.
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Tomar et al. (2024) studied this question.
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