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Immune Based Event-Incident Model for Intrusion Detection Systems: A Nature Inspired Approach to Secure Computing

Vasudevan, Swetha
http://rave.ohiolink.edu/etdc/view?acc_num=kent1182821562

Abstract Details

2007, MS, Kent State University, College of Arts and Sciences / Department of Computer Science.
Immune System is essential for the survival of the species. How exactly this sophisticated defense mechanism accomplishes the level of discrimination remains deeply enigmatic. Both Immune System and Intrusion Detection System work toward a comparable goal, identifying and responding to malicious agents. The effectiveness of an Intrusion Detection System however, depends on its ability to accurately differentiate between an event and an incident. Today computer scientists and researchers are borrowing some of the underlying principles of Immunology to implement such a system. The Human Immune System primarily involves highly specific recognition of foreign antigens and tolerance of self antigens. For more than six decades, the concept of ‘self / non-self’ formed the central theme of Immunology. The model states that all foreign entities that are not part of the organism trigger an immune response, whereas self elements do not. In the last few years, several researchers have challenged the authenticity of this concept and have come up with rival ideas. One such notion is the Danger Theory for Immunology. According to this new viewpoint, the Immune System does not discriminate between self and non-self elements but between danger and non-danger. Danger is perceived as a signal emitted by the cells that die an unnatural death. Detection of a foreign entity occurs in conjunction with the detection of danger signals which are emanated as a result of discontinuity in the constant interactions between the immune receptors and their targets. In this thesis, the author proposes a new Danger Theory based Event-Incident Model for Intrusion Detection System. The proposed model also borrows some key characteristics of autonomous multi-agent system. It employs a group of detectors known as the ‘Mobile Intrusion Detection Squad’ and utilizes the ‘Divide and Conquer Approach’ to identify and respond to both distributed and coordinated attacks. The literature of Immune-based Intrusion Detection System currently lacks solution for ensuring corruption free immune detectors. The proposed model strives to address this issue by implementing attack resistant mobile agents which can relocate itself inside the network and be elusive when a suspicious activity is sensed. Special emphasis will be given to some prevailing challenges such as alert correlation and false alarm production. This thesis will provide a conceptual view and the overall infrastructure of the proposed model. It is the author’s hope that this Computer Immune Model will emulate some if not all of the brilliant characteristics of Mother Nature’s defense mechanism against diseases.
Michael Rothstein (Advisor)
65 p.
Computer Science
Intrusion Detection Systems; Immune System; Immune Detectors; Intrusion Detection Squad; Multi-Agent System

Recommended Citations

Citations

  • Vasudevan, S. (2007). Immune Based Event-Incident Model for Intrusion Detection Systems: A Nature Inspired Approach to Secure Computing [Master's thesis, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1182821562

    APA Style (7th edition)

  • Vasudevan, Swetha. Immune Based Event-Incident Model for Intrusion Detection Systems: A Nature Inspired Approach to Secure Computing. 2007. Kent State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1182821562.

    MLA Style (8th edition)

  • Vasudevan, Swetha. "Immune Based Event-Incident Model for Intrusion Detection Systems: A Nature Inspired Approach to Secure Computing." Master's thesis, Kent State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=kent1182821562

    Chicago Manual of Style (17th edition)

kent1182821562
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© 2007, all rights reserved.
This open access ETD is published by Kent State University and OhioLINK.