An Adaptive Defense Model for Cloud Computing Data Security

Due to the widespread application of cloud computing data, this paper proposes a cloud computing data defense model integrating Random Binary Extension Codes (RBEC) encoding and an adaptive Dynamic Heterogeneous Redundancy (DHR) technique.The core novelties lie in utilizing RBEC to strengthen data redundancy and incorporating reputation calculation and heterogeneity optimization in the DHR model to enhance adaptivity.Experimental analyses demonstrate the RBEC encoding achieves over 96% transformation success rate and 94s average time with optimized parameters.Comparisons of execution entity credibility, error counts and defense capability further validate the effectiveness of the adaptive optimizations in improving model security and attack resilience.This study provides an efficient mimetic defense methodology for robust cloud data protection.