Enhanced Fuzzy Particle Swarm Optimization Load Distribution (EFPSO-LD) for DDOS Attacks Detection and Prevention in Healthcare Cloud Systems,ERICDATA高等教育知識庫
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篇名
Enhanced Fuzzy Particle Swarm Optimization Load Distribution (EFPSO-LD) for DDOS Attacks Detection and Prevention in Healthcare Cloud Systems
並列篇名
Enhanced Fuzzy Particle Swarm Optimization Load Distribution (EFPSO-LD) for DDOS Attacks Detection and Prevention in Healthcare Cloud Systems
作者 A. Peter Soosai AnandarajG. Indumathi
英文摘要
Distributed Denial of Service (DDoS) is an attack that threats the availability of the healthcare related cloud services. In order to assure the each and every one time accessibility of patient’s data, propose a new solution that allows, firstly, the hypervisor to establish credible trust relationships among VMs by considering purpose and personal trust sources and employing vectors to aggregate them. Secondly Enhanced Fuzzy Particle Swarm Optimization (EFPSO) algorithm which guides the hypervisor to determine the optimal loads distribution among VMs in real-time that maximizes DDoS attacks’ detection. EFPSO algorithm which allocates incoming client request to available virtual machines depending on the load i.e. VM with least work load is found and then new request is allocated in the attack detection. The proposed EFPSO algorithm gives the hypervisor with the optimal detection load distribution strategy over VMs that maximizes the detection of DDoS attacks under a limited budget of resources. At finally prevention is performed by using Convex Support Vector Machine (CSVM) classifier. Experimental results are measured in terms of attacks’ detection, false positives, negatives, and CPU, memory during DDoS attacks.
起訖頁 435-446
關鍵詞 Cloud computingDistributed Denial of Service (DDoS)Load distributionConvex Support Vector Machine (CSVM) and attack detection
刊名 網際網路技術學刊  
期數 202003 (21:2期)
出版單位 台灣學術網路管理委員會
DOI 10.3966/160792642020032102012   複製DOI
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