摘要
受到疫苗和人体免疫系统工作方式的启发,本文提出一种入侵预防系统模型,它模拟人体注射疫苗后免疫系统产生相应抗体抵抗抗原的机理:通过设置捕获器捕获最新的外部入侵病毒并将其加入病毒特征库,通过特征匹配和异常检测两种方式检测识别病毒并将其隔离消除。
Illuminated by human immune system, this paper presents a continuous learning model for intrusion defense that follows the principle of how bacterin stimulates the immune system to generate antibody. This model presents how to get the important ＂bacterin＂ to add to the database, which is used to do signature matching and anomaly detection, and thus protect system from unknown intrusion （virus）.
出处
《微计算机信息》
北大核心
2007年第03X期50-51,83,共3页
Control & Automation
关键词
入侵防卫
陷阱
自学习
免疫系统
Intrusion defense, honey pot, Self-learning, immunity system
