Intrusion detection using geometrical structure

Aruna Jamdagni, Zhiyuan Tan, Priyadarsi Nanda, Xiangjian He, Ren Liu

    Research output: Chapter in Book / Conference PaperConference Paper

    12 Citations (Scopus)

    Abstract

    ![CDATA[We propose a statistical model, namely geometrical structure anomaly detection (GSAD) to detect intrusion using the packet payload in the network. GSAD takes into account the correlations among the packet payload features arranged in a geometrical structure. The representation is based on statistical analysis of Mahalanobis distances among payload features, which calculate the similarity of new data against pre-computed profile. It calculates weight factor to determine anomaly in the payload. In the 1999 DARPA intrusion detection evaluation data set, we conduct several tests for limited attacks on port 80 and port 25. Our approach establishes and identifies the correlation among packet payloads in a network.]]
    Original languageEnglish
    Title of host publicationProceedings of the Fourth International Conference on Frontier of Computer Science and Technology, FCST 2009 (17-19 Dec. 2009 )
    PublisherIEEE
    Pages327-333
    Number of pages7
    ISBN (Print)9780769539324
    Publication statusPublished - 2009
    EventInternational Conference on Frontier of Computer Science and Technology, FCST 2009 -
    Duration: 1 Jan 2009 → …

    Conference

    ConferenceInternational Conference on Frontier of Computer Science and Technology, FCST 2009
    Period1/01/09 → …

    Keywords

    • computer networks
    • intrusion detection systems (computer security)

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