Keystroke Identification with a Genetic Fuzzy Classifier

摘要：

This paper proposes the use of fuzzy if-then rules for Keystroke identification. The proposed methodology modifies Ishibuchi’s genetic fuzzy classifier to handle high dimensional problems such as keystroke identification. High dimensional property of a problem increases the number of rules with low fitness. For decreasing them,rule initialization and coding are modified. Furthermore a new heuristic method is developed for improving the population quality while running GA. Experimental result demonstrates that we can achieve better running time,interpretability and accuracy with these modifications.

关键词： Keystroke Identification:Fuzzy Logic:Genetic Algorithm:Fuzzy Rule Generation

作者: Fazel Bazrafshan Ahmad Javanbakht Hamed Mojallali

作者单位: Department of Computer Engineering Islamic Azad University,Gonbad Branch Gonbad Kavoos,Iran Department of Electrical Engineering Faculty of Engineering,University of Guilan Rasht,Iran

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Computer Engineering and Technology(2010年第二届计算机工程与技术国际会议 ICCET 2010)

会议地点: 成都

会议语种:英文

页码: 2243-2247

在线出版日期: 2010-04-16（万方平台首次上网日期，不代表论文的发表时间）