• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

GEP-based Framework for Immune- Inspired Intrusion Detection

Vol. 4, No. 6, December 22, 2010
10.3837/tiis.2010.12.017, Download Paper (Free):


Immune-inspired intrusion detection is a promising technology for network security, and well known for its diversity, adaptation, self-tolerance, etc. However, scalability and coverage are two major drawbacks of the immune-inspired intrusion detection systems (IIDSes). In this paper, we propose an IIDS framework, named GEP-IIDS, with improved basic system elements to address these two problems. First, an additional bio-inspired technique, gene expression programming (GEP), is introduced in detector (corresponding to detection rules) representation. In addition, inspired by the avidity model of immunology, new avidity/affinity functions taking the priority of attributes into account are given. Based on the above two improved elements, we also propose a novel immune algorithm that is capable of integrating two bio-inspired mechanisms (i.e., negative selection and positive selection) by using a balance factor. Finally, a pruning algorithm is given to reduce redundant detectors that consume footprint and detection time but do not contribute to improving performance. Our experimental results show the feasibility and effectiveness of our solution to handle the scalability and coverage problems of IIDS.


Show / Hide Statistics

Statistics (Cumulative Counts from December 1st, 2015)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.

Cite this article

[IEEE Style]
W. Tang, L. Peng, X. Yang, X. Xie and Y. Cao, "GEP-based Framework for Immune- Inspired Intrusion Detection," KSII Transactions on Internet and Information Systems, vol. 4, no. 6, pp. 1273-1293, 2010. DOI: 10.3837/tiis.2010.12.017.

[ACM Style]
Wan Tang, Limei Peng, Ximin Yang, Xia Xie, and Yang Cao. 2010. GEP-based Framework for Immune- Inspired Intrusion Detection. KSII Transactions on Internet and Information Systems, 4, 6, (2010), 1273-1293. DOI: 10.3837/tiis.2010.12.017.