Multistage Anomaly Detection over Intelligence Threats Evolution for Secured Cloud Computing Resources

Many research institutions (ENISA, CSA, SUN, etc.) on cloud computing are always referred to a DDoS attacks item wamingly. In this paper, we describe the evolution of intelligence threats to APTs from various DDoS attacks, symptoms of DDoS attacks, and multistage anomaly detection scheme of anomaly...

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Published inInternational Information Institute (Tokyo). Information Vol. 16; no. 12; p. 8469
Main Authors Ji, YooKang, Kim, YongIl, Kim, JongWon, Cha, ByungRae
Format Journal Article
LanguageEnglish
Published Koganei International Information Institute 01.12.2013
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Abstract Many research institutions (ENISA, CSA, SUN, etc.) on cloud computing are always referred to a DDoS attacks item wamingly. In this paper, we describe the evolution of intelligence threats to APTs from various DDoS attacks, symptoms of DDoS attacks, and multistage anomaly detection scheme of anomaly for secured cloud computing resource. Specially, Lightweight anomaly detection stage could classified volume data into large volume data and small volume data, and applied Bayesian techniques to detect anomaly and symptoms of various attack. And focused anomaly detection stage is performed to detect novel attacks by unsupervised learning algorithm. [PUBLICATION ABSTRACT]
AbstractList Many research institutions (ENISA, CSA, SUN, etc.) on cloud computing are always referred to a DDoS attacks item wamingly. In this paper, we describe the evolution of intelligence threats to APTs from various DDoS attacks, symptoms of DDoS attacks, and multistage anomaly detection scheme of anomaly for secured cloud computing resource. Specially, Lightweight anomaly detection stage could classified volume data into large volume data and small volume data, and applied Bayesian techniques to detect anomaly and symptoms of various attack. And focused anomaly detection stage is performed to detect novel attacks by unsupervised learning algorithm.
Many research institutions (ENISA, CSA, SUN, etc.) on cloud computing are always referred to a DDoS attacks item wamingly. In this paper, we describe the evolution of intelligence threats to APTs from various DDoS attacks, symptoms of DDoS attacks, and multistage anomaly detection scheme of anomaly for secured cloud computing resource. Specially, Lightweight anomaly detection stage could classified volume data into large volume data and small volume data, and applied Bayesian techniques to detect anomaly and symptoms of various attack. And focused anomaly detection stage is performed to detect novel attacks by unsupervised learning algorithm. [PUBLICATION ABSTRACT]
Author Cha, ByungRae
Kim, YongIl
Ji, YooKang
Kim, JongWon
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SubjectTerms Anomalies
Bandwidths
Case studies
Cloud computing
Data integrity
Denial of service attacks
Evolution
Intelligence
Internet
Learning
Legacy systems
Multistage
Peer to peer computing
Poisoning
Threats
Weight reduction
Title Multistage Anomaly Detection over Intelligence Threats Evolution for Secured Cloud Computing Resources
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