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A Distributed Intrusion Detection Model via Nondestructive Partitioning and Balanced Allocation for Big Data 被引量:4
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作者 Xiaonian Wu chuyun zhang +2 位作者 Runlian zhang Yujue Wang Jinhua Cui 《Computers, Materials & Continua》 SCIE EI 2018年第7期61-72,共12页
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 detec... 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 enjoys favorable advantages such as good load balance,higher detection rate and detection efficiency. 展开更多
关键词 Distributed intrusion detection data allocation load balancing data integrity big data
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