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Genetic Algorithm Rule Definition for Denial of Services Network Intrusion Detection

Genetic Algorithm Rule Definition for Denial of Services Network Intrusion Detection. IEEE Coputational Intelligence and Natural Computing, vol 1, pp. 99-102, June 2009 Authors ： Yong Wang, Dawu Gu, Xiuxia Tian and Jing Li Present ： Jheng-Hen Jiang. Outline. Introduction Related Work

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Genetic Algorithm Rule Definition for Denial of Services Network Intrusion Detection

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  1. Genetic Algorithm Rule Definition forDenial of ServicesNetwork Intrusion Detection IEEE Coputational Intelligence and Natural Computing, vol 1, pp. 99-102, June 2009 Authors：Yong Wang, Dawu Gu, Xiuxia Tianand Jing Li Present：Jheng-Hen Jiang

  2. Outline • Introduction • Related Work • Proposed Scheme • Experimental Result • Conclusions

  3. Indroduction • Expanding previous work and present a fitness function. • The rule will be changed by itself.

  4. Raw Intrusion Data Set Start End Data Refiner Encoding Chromosomes Generate Initial Population Evaluate Fitness Value with Rule Meets Criteria Genetic Algorithm Data Classify Normal Attacks

  5. Proposed Scheme(1/2) • Chromosome Rule Encoding Dos Records • Attr(Duration, Protocol, Service, …, Attack type) • Attr(0, icmp, ecr_i, SF, 1032, …, smurf) • Gene(0, 1, 2, 4, 408, …, 12) Hexadecimal

  6. N：Attackeventsmatrix j：Anumberofattacktype W：Aratioofnumberfeatureinthedatasettothetotalnumberfeatureinthe dataset Xn：The nth gene Wn：The weight of nth gene рn：The nth gene’s attribute CV：Correctedvector

  7. Experimental Result

  8. Conclusions • Do not have to update the rule everyday. • Suitable to continuously changing misuse detection.

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