Based on the Fuzzy Recognition of Malicious Code Detection Technology Research

In the process of malicious code detection, it is assumed that the malicious code hidden deep, it is difficult to complete and accurate of malicious code features are extracted. Malicious code detection using the traditional algorithm, the distribution of malicious code is unknown, without fully considering the characteristic differences between different categories code, reduces the accuracy of the malicious code detection. To this end, the malicious code detection based on fuzzy recognition method is proposed. According to the theory of support vector machine (SVM) related to extract characteristics of malicious code, and will be the basis of the above characteristics as malicious code identification. Establish a fuzzy recognition to identify tree, calculated to identify objects belong to the probability of malicious code, for detecting malicious code. The experimental results show that the improved algorithm of malicious code detection, can greatly improve the accuracy of detection.