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Adaptive Hierarchical Intrusion Tolerant Model Based on Autonomic Computing

机译:基于自主计算的自适应分层入侵耐受模型

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Intrusion tolerance has been a key technology of system survivability. Aiming at the absence of self-adaptation ability and quantitative analysis on existent intrusion tolerant system, an adaptive hierarchy intrusion tolerant system based on Autonomic Computing (AHITAC, for short) is proposed. Adopting hierarchy modes, the critical modules of AHITAC include confidence evaluation of accessing, active trapping on suspicious information, hierarchical learning of applications and classed recovery of system function. By autonomic implementing the learning and adaptive function of confidence threshold, service classification and trap repository, AHITAC implements the tolerance on intrusion and suspicious information, improving the ability of self-recovery and self-optimization on object network. The simulation results show that the object network with AHITAC is stable and tolerant.
机译:入侵耐受是系统生存能力的关键技术。旨在缺乏自适应能力和存在的入侵耐受系统的定量分析,提出了一种基于自主计算的自适应层次入侵耐受系统(AHITAC,短暂)。采用层次结构模式,AHITAC的关键模块包括对可疑信息的访问,主动诱捕的置信度评估,应用程序的分层学习和系统功能的课程恢复。通过自主实现置信阈值的学习和自适应函数,服务分类和陷阱存储库,Ahitac实现了对入侵和可疑信息的容忍度,提高了对象网络上自我恢复和自我优化的能力。仿真结果表明,具有Ahitac的物体网络是稳定和耐受的。

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