摘要
提出了一种基于人工免疫的病毒检测方法,给出了计算机软件系统中自体、非自体、抗原、免疫细胞等的表示方法,实现了否定选择和克隆选择等免疫机制。通过实验测试了该方法的识别能力、错误否定率和错误肯定率,结果表明该方法具有自适应、自学习和多样性等特点,能够有效地检测未知计算机病毒。
An immune-based method for virus detection is proposed in this paper. The formal definitions of serf, nonself, antigen, antibody, immunocyte in computer software system are presented, Some immune mechanism, such as negative selection and clone selection, are implemented. Experiments are done to test the detection ability, false-negative rate and false-positive rate of the method, Result shows that this method has the features of self-adaptation, self-learning, diversity, can detect know and unknow computer virus effectively.
出处
《计算机应用研究》
CSCD
北大核心
2005年第9期111-112,114,共3页
Application Research of Computers
基金
国家自然科学基金资助项目(60373110)
教育部博士点基金资助项目(200306100003)
关键词
计算机病毒检测
人工免疫系统
否定选择
克隆选择
Computer Virus Detection
Artificial Immune System
Negative Selection
Clone Selection
