2013 Fiscal Year Final Research Report
Study of Anomaly Detection Method using Hurst Space.
| Project/Area Number |
23500077
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Computer system/Network
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| Research Institution | Akita University |
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Principal Investigator |
TAKAHASHI Akinori 秋田大学, 工学(系)研究科(研究院), 助教 (90236258)
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| Project Period (FY) |
2011 – 2013
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| Keywords | ネットワークトラフィック / 異常検知 / 自己相似性 / ハーストパラメータ / R/S Pox レッグライン特性 / トラフィック可視化手法 |
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| Research Abstract |
This study proposes a newly defined expression of traffic characteristic to quantify a non-stationarity of the Internet traffic time series, and an anomaly detection method for periodic time series using that characteristic as well. The proposed method showed that it was effective for the detection of low-rate attacks having such a cycle as long-term port scan.Furthermore, from the viewpoint of supporting a network manager, we proposed helpful visualization methods to the manager by using the Hurst space to step up the visibility of the characteristic changes.
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