An Adaptive Intrusion Tolerance Model Based on Autonomic Computing

Qing Tao Wu; Bin Hua; Rui Juan Zheng; Ming Chuan Zhang

doi:10.4028/www.scientific.net/AMM.44-47.3259

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 44-47An Adaptive Intrusion Tolerance Model Based on...

An Adaptive Intrusion Tolerance Model Based on Autonomic Computing

Abstract:

Intrusion tolerance has been a key technology of system survivability. To cope with the absence of self-adaptability on existent intrusion tolerance system, an intrusion tolerant model based on autonomic computing is proposed, in which the reliability of the network connection is analyzed in real time to generate the initial reliability by an autonomic feedback mechanism, and the classification between suspicious information and confident information is guaranteed for implementing the tolerance on suspicious connections through the dynamic reliability optimization. The simulation results show that the intrusion tolerant model with autonomic feedback mechanism is desirable for enhancing the system’s self-adaptive performance, making it highly promising for further study.

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Periodical:

Applied Mechanics and Materials (Volumes 44-47)

Pages:

3259-3263

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.44-47.3259

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Online since:

December 2010

Authors:

Qing Tao Wu, Bin Hua, Rui Juan Zheng, Ming Chuan Zhang

Keywords:

Autonomic Computing, BP Neural Network (BPNN), Intrusion Tolerance, Reliability Evaluation

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