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Information Journal Paper

Title

STLR: ANOVEL DANGER THEORY BASED STRUCTURAL TLR ALGORITHM

Pages

  209-225

Abstract

 Arti cial Immune Systems (AIS) have long been used in the eld of computersecurity and especially in Intrusion Detection systems. Intrusion detectionbased on AISs falls into two main categories. The rst generation of AIS isinspired from adaptive immune reactions but, the second one which is calleddanger theory focuses on both adaptive and innate reactions to build a morebiologically-realistic model of Human Immune System. Two algorithms namedTLR and DCA are proposed in DANGER THEORY eld that both of them aretrying to identify the antigens based on a simple identi er. Both of them su erfrom low accuracy and detection rate due to the fact that they are not takingthe structure of antigens into account. In this paper, we propose an algorithmcalled STLR (structural TLR), which is an extended form of TLR ALGORITHM. STLR tries to model the interaction of adaptive and innate biological immunesystems and at the same time considers the structure of the antigens. Theexperimental results show that using the structural aspects of an antigen, STLR can lead to a great increase in the detection rate and accuracy.

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    APA: Copy

    AZMI, REZA, & PISHGOO, BOSHRA. (2013). STLR: ANOVEL DANGER THEORY BASED STRUCTURAL TLR ALGORITHM. THE ISC INTERNATIONAL JOURNAL OF INFORMATION SECURITY, 5(2 ), 209-225. SID. https://sid.ir/paper/241833/en

    Vancouver: Copy

    AZMI REZA, PISHGOO BOSHRA. STLR: ANOVEL DANGER THEORY BASED STRUCTURAL TLR ALGORITHM. THE ISC INTERNATIONAL JOURNAL OF INFORMATION SECURITY[Internet]. 2013;5(2 ):209-225. Available from: https://sid.ir/paper/241833/en

    IEEE: Copy

    REZA AZMI, and BOSHRA PISHGOO, “STLR: ANOVEL DANGER THEORY BASED STRUCTURAL TLR ALGORITHM,” THE ISC INTERNATIONAL JOURNAL OF INFORMATION SECURITY, vol. 5, no. 2 , pp. 209–225, 2013, [Online]. Available: https://sid.ir/paper/241833/en

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