Adaptive Hierarchical Intrusion Tolerant Model Based on Autonomic Computing

Abstract

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.