Abstract: Intrusion tolerance has been a key technology of system survivability. Concerning the absence of self-adaptability on existent intrusion tolerance systems, an intrusion tolerance model based on autonomic computing was proposed. The reliability of the network connection was analyzed in real-time to generate the initial reliability by an autonomic feedback law, and the classification between suspicious information and confident information was guaranteed for implementing the tolerance on suspicious connections through the dynamic reliability optimization. The simulation results show that the intrusion tolerance model with autonomic feedback law can strengthen the self-adaptive performance of system.

Key words: autonomic computing, reliability evaluation, intrusion detection, Back Propagation (BP) neural network

摘要： 针对当前入侵容忍系统缺乏自适应能力的问题，借鉴自律计算的思想，提出了一个自律容侵模型。利用自律反馈机制对网络连接的可信度进行实时分析，生成初始信度，并通过信度阈值的自主学习与调整实施动态信度优化，完成对可疑信息和可信信息的服务分流，实现对可疑连接的自律容忍。仿真结果表明，具有自律反馈机制的入侵容忍模型可以有效增强系统的自适应能力。

关键词: 自律计算, 可信度评估, 入侵容忍, BP神经网络