A Comprehensive Taxonomy and Systematic Review of Intelligent Attack Defense Systems for Multi-Cloud Environment
Keywords:
Multi cloud, Inter cloud, Nature Inspired algorithms, Evolutionary Computing, Attack Detection, Intrusion DetectionAbstract
Oftentimes, public cloud users and companies implemented multi-cloud in meeting their needs of cloud computing. Security and data confidentiality remains most important deliberations in selecting and studying cloud computing. Of late, developments in machine learning techniques have engrossed the attention of the research fraternity to create intrusion detection systems (IDS) to intelligently detect glitches in the network traffic flow. The purpose of this paper is to underline the significance on nature-inspired meta-heuristic intelligent algorithms and advantages in these methods on attack detection in multi-cloud environment. A thorough systematic review has been proffered. The findings obtained have shown that the hybrid intelligence-based algorithms have a substantial impact on resolving the issue of attack detection in multi-cloud, and such an effect has augmented in the recent years. Apart from that, this paper focuses on providing more effective algorithms and research directions for attack detection and avoidance in multi-cloud in the future.
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