An Efficient Fuzzy Self-Classifying Clustering based Framework for Cloud Security

International Journal of Computational Intelligence Systems

关键词: Fuzzy neural networks;    Intrusion detection;    Hybrid intelligent systems;    Partitioning algorithms;    Pattern analysis;   

DOI  :  10.2991/ijcis.2017.10.1.34

来源: DOAJ

【 摘 要 】

Though cloud computing has become an attractive technology due to its openness and services, it brings several security hazards towards cloud storage. Since the distributed nature of clouds is achieved through internetworking technologies, clouds suffer from all the vulnerabilities by which networking also suffers. In essence, data stored in clouds are vulnerable to attacks from intruders. But, no single technique can provide efficient intrusion detection. In this paper, we propose fuzzy self-classifying clustering based cloud intrusion detection system which is intelligent to gain knowledge of fuzzy sets and fuzzy rules from data to detect intrusions in a cloud environment. Its efficiency is explained by comparing with other three cloud intrusion detection systems. Using a standard benchmark data from a CIDD (Cloud Intrusion Detection Dataset), experiments are conducted and tested. The results are presented in terms of success rate accuracy.

【 授权许可】

Unknown