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In this paper,we propose a novel Intrusion Detection System (IDS) architecture utilizing both the evidence theory and Rough Set Theory (RST). Evidence theory is an effective tool in dealing with uncertainty question. It relies on the expert knowledge to provide evidences,needing the evidences to be independent,and this make it difficult in application. To solve this problem,a hybrid system of rough sets and evidence theory is proposed. Firstly,simplification are made based on Variable Precision Rough Set (VPRS) conditional entropy. Thus,the Basic Belief Assignment (BBA) for all evidences can be calculated. Secondly,Dempster’s rule of combination is used,and a decision-making is given. In the proposed approach,the difficulties in acquiring the BBAs are solved,the correlativity among the evidences is reduced and the subjectivity of evidences is weakened. An illustrative example in an intrusion detection shows that the two theories combination is feasible and effective.
In this paper, we propose a novel Intrusion Detection System (IDS) architecture utilizing both the evidence theory and Rough Set Theory (RST). Evidence theory is an effective tool in dealing with uncertainty question. It relies on the expert knowledge to provide evidences, needing the evidences to be independent, and this make it difficult in application. , the Basic Belief Assignment (BBA) for all evidences can be calculated. Dempster’s rule of combination is used, and a decision-making is given. In the proposed approach, the difficulties in acquiring the BBAs are solved, the correlativity among the evidences is reduced and the subjectivity of evidences is weakened. An example example in an intrusion detection shows that the two theories combination is feasible and effective.