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个人信息Personal Information
教授
博士生导师
硕士生导师
主要任职:Director of Academic Committee at Kaifa District
其他任职:开发区校区学术分委员会主任(Director of Academic Committee at Kaifa Campus)
性别:男
毕业院校:多伦多大学
学位:博士
所在单位:软件学院、国际信息与软件学院
学科:软件工程. 运筹学与控制论
办公地点:开发区(Kaifa District Campus)
联系方式:mingchul@dlut.edu.cn
电子邮箱:mingchul@dlut.edu.cn
Efficient context-sensitive intrusion detection based on state transition table
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论文类型:会议论文
发表时间:2011-01-01
收录刊物:EI、Scopus
卷号:E94-A
期号:1
页面范围:255-264
摘要:Those host-based intrusion detection models like VPStatic first construct a model of acceptable behaviors for each monitored program via static analysis, and then perform intrusion detection by comparing them with programs' runtime behaviors. These models usually share the highly desirable feature that they do not produce false alarms but face the conflicts between accuracy and efficiency. For instance, the high accuracy of the VP- Static model is at the cost of high space complexity. In this paper, we use a statically-constructed state transition table (SiT), which records expected transitions among system calls as well as their stack states (return address lists), as a behavior model to perform context-sensitive intrusion detection. According to our analysis, our STE model improves the space efficiency of the VPStatic model without decreasing its high precision and time effi ciency. Experiments show that for three test programs, memory uses of our STE models are all much less than half of the VPStatic models'. Thereby, we alleviate the conflicts between the accuracy and the efficiency. Copyright ? 2011 The Institute of Electronics, Information and Communication Engineers.