doi:10.3850/978-981-08-7304-2_1458

ABSTRACT

In this paper, I have successfully presented an extended fuzzy Petri net (EFPN) model to derive the final detection decision as an inference engine. Based on the EFPN model, an efficient algorithm is proposed to automatically reason about imprecise and fuzzy information. By using the reasoning algorithm for the EFPN, I present an alternative approach which is more promising than the fuzzy logic. The proposed FPN approach offers more flexible reasoning capability because it is able to obtain results with fuzzy intervals rather than point values. I have built the fuzzy Petri net model and classified the input data in terms of ΔSEQ and ΔT and obtained the output data of P, so the system can be viewed as the two-input and one output system. The experimental results of an illustration example of TCP SYN flooding of tack defection is provided show the proposed approach is feasible and acceptable to derive the final detection decision as an inference engine.

Keywords: Extended fuzzy Petri net, Fuzzy reasoning, Intrusion detection, Modeling.

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