Technical gazette, Vol. 32 No. 1, 2025.
Original scientific paper
https://doi.org/10.17559/TV-20240121001277
An Adaptive Defense Model for Cloud Computing Data Security
Xing Yang
; Geely University of China, Chengdu, Sichuan, 610000, China
*
Ke Xiang
; Sichuan Post and Telecommunication College, Chengdu, Sichuan, 610000, China
Jilan Huang
; Geely University of China, Chengdu, Sichuan, 610000, China
* Corresponding author.
Abstract
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.
Keywords
binary random extension code; dynamic heterogeneous redundancy; file encryption system; key update; moving target defense
Hrčak ID:
325975
URI
Publication date:
31.12.2024.
Visits: 10 *