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학술대회 Baseline Traffic Modeling for Anomalous Traffic Detection on Network Transit Points
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저자
조유희, 강구홍, 김익균, 정기태
발행일
200909
출처
Asia-Pacific Network Operations and Management Symposium (APNOMS) 2009 (LNCS 5787), v.5787, pp.385-394
출판사
Springer
DOI
https://dx.doi.org/10.1007/978-3-642-04492-2_39
협약과제
09MS5300, 분산서비스거부(DDoS) 공격 대응 기술개발, 장종수
초록
Remarkable concerns have been made in recent years towards detecting the network traffic anomalies in order to protect our networks from the persistent threats of DDos and unknown attacks. As a pre-process for many state-of-the-art attack detection technologies, baseline traffic modeling is a prerequisite step to discriminate anomalous flow from normal traffic. In this paper, we analyze the traffic from various network transit points on ISP backbone network and present a baseline traffic model using simple linear regression for the imported NetFlow data; bits per second and flows per second. Our preliminary explorations indicate that the proposed modeling is very effective to recognize anomalous traffic on the real networks. © 2009 Springer Berlin Heidelberg.
키워드
Anomaly, DDoS attack, Intrusion Detection
KSP 제안 키워드
Anomalous traffic detection, Attack Detection, Backbone Network, DDoS attacks, Netflow data, Network Traffic, Normal traffic, Real networks, Simple linear regression, Traffic anomalies, intrusion detection