Mehran University Research Journal Of Engineering &
Technology (HEC Recognized In Category "X")
Publishing Since 1982.



For Authors
For Readers
Article Information  
An Adaptive Fuzzy Framework based on Optimized Fuzzy Contexts for Detecting Network Intrusions

Keywords: Anomaly IDS, Fuzzy Logic, Genetic Algorithms, Fuzzy Context, Context Switching.

Mehran University Research Journal of Engineering & Technology

Volume 29 ,  Issue 4

Habib Ullah   Baig , Mahmood  Ahmad  Sheikh , Farrukh   KAMRAN ,

References
1. Symantec, "Rise in Data Theft, Data Leakage, and Targeted Attacks Leading to Hackers", In Financial Gain news Release S. Reports, 2007.
2. Halme, L.R., "AIN'T Misbehaving -- A Taxonomy of Anti-Intrusion Techniques", Computers and Security, volume 40, No. 7, pp. 606, 1995.
3. Lee, W. and Stolfo S.J., "A Framework for Constructing Features and Models for Intrusion Detection Systems", ACM Transaction on Information and System Security, Volume 3, No. 4, pp. 227-261, 2000.
4. Vasilios, A.S. and Papagalou F., "Application of anomaly detection algorithms for detecting SYN flooding attacks", Proceedings of IEEE communications Society Globecom, 2004.
5. Wang, H., Zhang D., and Shin K.G., "Change Point monitoring for detection of Dos attacks", IEEE Transaction of dependable and secure computing, volume 1, No. 4, 2004.
6. Barbara, D., Couto J., Jajodia S., and Wu N., "Special section on data mining for intrusion detection and threat analysis: Adam: a test-bed for exploring the use of data mining in intrusion detection", ACM SIGMOD Record volume 30, pp. 15-24, 2001.
7. Barbara, D., Wu N., and Jajodia S., "Detecting Novel Network Intrusions Using Bayes Estimators", Proceedings of First SIAM International Conference on Data Mining, SDM 2001, Chicago, USA, 2001.
8. Yoshida, K., "Entropy based intrusion detection", Proceedings of IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM2003), 2003.
9. Lee, W., Stolfo S.J., and Mok K.W., "Mining audit data to build intrusion detection models", in Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, KDD ’98, New York, NY, USA, 1998.
10. Botha, M. and Solms R.V., "Utilizing fuzzy logic and trend analysis for effective intrusion detection", Computers & Security, Volume 22, No. 5, pp. 423-434, 2003.
11. Gomez, J. and Dasgupta D., "Evolving fuzzy classifiers for intrusion detection", Proceedings of in Proceedings of the 2002 IEEE Workshop on the Information Assurance, West Point, NY, USA, 2001.
12. Pillai, M.M., J.H.P E., and H.S V., "An Approach to Implement a Network Intrusion Detection System using Genetic Algorithms", Proceedings of SAICSIT, 2004.
13. Crosbie, M., "Applying genetic programming to intrusion detection", Proceedings of AAAI Fall Symposium series, 1995.
14. Zitzler, E. and Thiele L., "Multi-objective Evolutionary Algorithms: A comparative Case Study and the Strength Pareto Approach", IEEE Transaction on Evolutionary Computation, volume 3, No. 4, pp. 257-271, 1999.
15. Dickerson, J.E. and Dickerson J.A., "Fuzzy network profiling for intrusion detection", Proceedings of 19th International Conference of the North American Fuzzy Information Processing Society, Atlanta, USA, 2000.
16. Liao, Y., Vemuri V. R., and Pasos A., "Adaptive anomaly detection with evolving connectionist systems", Network and Computers Applications, Volume 30, No. 2007, pp. 60-80, 2005.
17. Abadeh, M.S., Habibi J., and Lucas C., "Intrusion detection using a fuzzy genetics-based learning algorithm", Journal of Network and Computer Applications, Volume 30, No. 2007, pp. 414-428, 2007.
18. Tsang, C.-H., Lwong S., and Wang H., "Anomaly Intrusion Detection using Multi-Objective Genetic Fuzzy System and Agent-based Evolutionary Computation Framework", Proceedings of Fifth IEEE International Conference on Data Mining (ICDM'05), 2005.
19. Yen, J. and Langari R., "Fuzzy Logic: Intelligence, Control and Information", Prentice Hall, Upper Saddle River NJ, 1999.
20. DARPA, "Darpa 98/99 Data Set": MIT Lincoln Labs, 1998.
21. Baig, H.U. and Kamran F., "Detection of Low Intensity DoS attacks using Fuzzy Intrusion Detection System", Proceedings of ICICE Conference, Dhaka Bangladesh, 2006.