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 in | International Information Institute (Tokyo). Information Vol. 16; no. 12; p. 8469 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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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] |
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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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