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

• 作者: Chuyun Zhang Jinhua Cui Runlian Zhang Xiaonian Wu Yujue Wang
• 来源期刊: 计算机、材料和连续体(英文)
• 学科: 工学
• 关键词: DISTRIBUTED INTRUSION detection DATA ALLOCATION load balancing DATA integrity big DATA
• 年，卷（期）: 2018,（7）
• 页码范围: 61-72
• 页数: 12页
• 分类号: TP3

摘要

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.