Title :
Study of Multistage Anomaly Detection for Secured Cloud Computing Resources in Future Internet
Author :
Cha, ByungRae ; Kim, JongWon
Abstract :
Future Internet Groups have been studying networking virtualization and computing virtualization for Test bed. Specially, GENI have adopted cloud computing as computing virtualization technique. In this paper, we describe the multistage anomaly detection scheme of anomaly and symptoms of DDoS attacks for secured cloud computing resource. This scheme is composed by 3 stages. Monitoring stage performs misuse detection by rules of attack patterns to well known DDoS attacks. Lightweight anomaly detection stage could classified volume data into large volume data and small volume data, and applied Bayesian methods to detect anomaly and symptoms of DDoS attack. And focused anomaly detection stage is performed to detect novel DDoS attacks by unsupervised learning algorithm.
Keywords :
Bayes methods; Internet; cloud computing; computer network security; learning (artificial intelligence); virtual machines; Bayesian methods; DDoS attacks; GENI; attack pattern rules; computing virtualization; future Internet groups; misuse detection; multistage anomaly detection; networking virtualization; secured cloud computing resources; testbed; unsupervised learning algorithm; Cloud computing; Computer crime; Data analysis; IP networks; Monitoring; Cloud Computing; DDoS Attack; Dark IP; Multistage Anomaly Detection; P2P DDoS;
Conference_Titel :
Dependable, Autonomic and Secure Computing (DASC), 2011 IEEE Ninth International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-4673-0006-3
DOI :
10.1109/DASC.2011.171