Title :
A Kind of Malicious Code Detection Scheme Based on Fuzzy Reasoning
Author :
Guo Gang ; Chen Zhongquan
Author_Institution :
Sch. of Comput. Sci., Beijing Inst. of Technol., Beijing, China
Abstract :
This thesis presents a malicious-degree decision system based on dynamic fuzzy neural network. Integrated with fuzzy reasoning and neural network in artificial intelligence, this system gives a comprehensive evaluation such as malicious-degree by analyzing the behaviors of unknown code. This method is compared with simple and multiple Bayes in the end. The experimental results and comparison show that this decision system can achieve good results in detecting polymorphic and unknown viruses.
Keywords :
computer viruses; fuzzy neural nets; fuzzy reasoning; fuzzy set theory; Bayes method; artificial intelligence; comprehensive evaluation; dynamic fuzzy neural network; fuzzy reasoning; malicious code detection scheme; malicious-degree decision system; polymorphic unknown virus detection; unknown code behavior analysis; Accuracy; Artificial neural networks; Bayes methods; Fuzzy neural networks; Fuzzy reasoning; Mathematical model; artificial neural network; fuzzy reasoning; malicious code detection;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2014 7th International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-6635-6
DOI :
10.1109/ICICTA.2014.12
