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    A Distributed Intrusion Detection Model via Nondestructive Partitioning and Balanced Allocation for Big Data

    Xiaonian Wu1,*, Chuyun Zhang3, Runlian Zhang2, Yujue Wang2, Jinhua Cui4

    CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 61-72, 2018, DOI:10.3970/cmc.2018.02449

    Abstract There are two key issues in distributed intrusion detection system, that is, maintaining load balance of system and protecting data integrity. To address these issues, this paper proposes a new distributed intrusion detection model for big data based on nondestructive partitioning and balanced allocation. A data allocation strategy based on capacity and workload is introduced to achieve local load balance, and a dynamic load adjustment strategy is adopted to maintain global load balance of cluster. Moreover, data integrity is protected by using session reassemble and session partitioning. The simulation results show that the new model More >

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