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Network Intrusion Detection Using GA

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Presentation on theme: "Network Intrusion Detection Using GA"— Presentation transcript:

1 Network Intrusion Detection Using GA
by Krishnendu Roy 11/13/2018 CSC 7333

2 References W. Li, “Using Genetic Algorithm for Network Intrusion Detection”, Proceedings of the United States Department of Energy Cyber Security Group 2004 Training Conference, May 24-27, Kansas City, Kansas. R. H. Gong, M. Zulkernine, P. Abolmaesumi, “A Software Implementation of a Genetic Algorithm Based Approach to Network Intrusion Detection”, Sixth International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, 2005 and First ACIS International Workshop on Self-Assembling Wireless Networks. SNPD/SAWN 2005. 11/13/2018 CSC 7333

3 Outline Network Intrusion NID using GA Some Results Conclusion
11/13/2018 CSC 7333

4 Network Intrusion Breaking into a system
Performing an action not legally allowed Intruders External Internal 11/13/2018 CSC 7333

5 Network Intrusion – common ways
Exploiting software bugs and system misconfigurations, Password cracking, Sniffing unsecured traffic, Exploiting the design flaw of specific protocols 11/13/2018 CSC 7333

6 Intrusion Detection System
Goals: Detect Report to proper authority 11/13/2018 CSC 7333

7 Intrusion Detection Techniques
misuse detection detect known techniques IDS looks for pattern/signature anomaly detection 11/13/2018 CSC 7333

8 Types of IDS Network-based Host-based 11/13/2018 CSC 7333

9 Role of GA – generate the rule-set
IDS requires a set of rules GA generates this knowledge base efficiently 11/13/2018 CSC 7333

10 First Paper 11/13/2018 CSC 7333

11 Rule Generation Pre-classified data
Differentiates normal net. conn. vs. anomalous Small set of randomly generated rules 11/13/2018 CSC 7333

12 Rule Definition 11/13/2018 CSC 7333

13 11/13/2018 CSC 7333

14 Chromosome Structure 11/13/2018 CSC 7333

15 Evaluation of Rules If find valid anomaly – bonus otherwise penalty
11/13/2018 CSC 7333

16 Weights 11/13/2018 CSC 7333

17 Evaluation Contd. 11/13/2018 CSC 7333

18 Second Paper 11/13/2018 CSC 7333

19 Chromosome Structure 11/13/2018 CSC 7333

20 Rule and Chromosome Rule Chromosome 11/13/2018 CSC 7333

21 Fitness of a Rule Rule : 11/13/2018 CSC 7333

22 Results – DARPA data set
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23 Results 11/13/2018 CSC 7333

24 Conclusion Network Intrusion GA based rule generation for NID
Chromosome Structure Fitness Functions Some Results 11/13/2018 CSC 7333

25 Thanks 11/13/2018 CSC 7333

26 Experimental Setting 5000 Generations 500 Initial Rules
Crossover rate 0.5 (two point) Mutation Rate 0.02 Top 20 rules selected 11/13/2018 CSC 7333

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