Entropy-based Denial of Service Attack Detection in Cloud Data Center
Cloud data centers today usually lack network resource isolation.Meanwhile,it is easy to deploy and terminate large number of malicious virtual machines(VMs)in a few seconds while the administrator is probably difficult to identify these malicious VMs immediately.These features open doors for attackers to launch denial-of-service(DoS)attacks that target at degrading the quality of cloud service.This paper studies an attack scenario that malicious tenants use cloud resources to launch DoS attack targeting at data center subnets.Unlike traditional data flow based detections,which heavily depend on the pattern of data flows,we propose an approach that takes advantage of virtual machine status including CPU usage and network usage to identify the attack.We notice that malicious virtual machines exhibit similar status patterns when attack is launched.Based on this observation,information entropy is applied in monitoring the status of virtual machines to identify the attack behaviors.We conduct our experiments in the campuswide data center,and the results show our detection system can promptly and accurately response to DoS attacks.
Index Terms-Cloud Data Center DoS Attack Information Entropy Attack Detection
Jiuxin Cao Bin Yu Fang Dong Xiangying Zhu Shuai Xu
School of Computer Science and Engineering Southeast University Sipailou,Nanjing,China ,210096
国际会议
2014 2nd International Conference on Advanced Cloud and Big Data (CBD 2014)(2014年先进云计算和大数据国际会议)
安徽黄山
英文
201-207
2014-11-20（万方平台首次上网日期，不代表论文的发表时间）