An Enhanced Exploration and Exploitation of Modified Grey Wolf Optimizer for Fuzzy Rules Reduction in Cloud Intrusion Detection System (CIDS)

Optimization problems in the Cloud Intrusion Detection System (CIDS) contain numerous conflicting objectives, uni-modal and multi-modal functions difficulty level varying between linear to non-linear limits. The Grey Wolf Optimizer (GWO) is a meta-heuristic technique that implemented based on social behavior of wolves their hunting behavior. Significant improvement exploration exploitation search space GWO can be obtained by modifying control parameter a. Works have already been carried out many researchers different manner achieve better results. In similar content, authors this study also modified added weight factor position each wolf attain best possible Due high demand for cloud computing environment, intrusion detection network plays big role maintaining faith clients. Hence, CIDS required inspect packets identify abnormal For developing system IDS, created fuzzy rules represent relationship attributes nature activity (normal or abnormal). Modified (MGWO) algorithm applied eleven benchmark test good performance metrics. results presented paper are promising; MGWO used reduce CIDS. proposed compared with classical GWO, Particle Swarm (PSO), Cuckoo Search (CS) variant MGWO. experimental reveal there significant its performance.