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基于改进FastICA算法的工控网络恶意节点攻击检测系统设计

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为了确保工控系统的安全和可靠性,基于改进FastICA算法,设计工控网络恶意节点攻击检测系统.在工控网络服务器端集群中,从网络服务器端、攻击行为排重模块、恶意节点辨识模块和Fabric攻击行为检测组件等4部分设计工控网络恶意节点攻击检测系统的硬件模块.在此基础上计算Fast初始值,统计ICA单位的不确定性,改进FastICA算法.由此,联合相关攻击行为信息,推导恶意节点的攻击分离条件.实验结果表明,按照1∶1的负荷标准分配待测数据,所设计系统可以有效检测恶意节点攻击行为,得到的恶意节点实时检测数量值与额定值的拟合度接近100%,能够较好维护网络体系的运行稳定性.
Design of Malicious Node Attack Detection System in Industrial Control Network Based on Improved FastICA Algorithm
To ensure the safety and reliability of the industrial control system,this paper designs a malicious node attack detec-tion system in industrial control network based on improved FastICA algorithm.In the industrial control network server clus-ter,the hardware module of malicious node attack detection system in industrial control network is designed from four parts,network server,attack behavior de-duplication module,malicious node identification module and Fabric attack behavior detec-tion component.On this basis,this paper calculates the initial value of Fast,tallies the uncertainty of ICA units,and improves the FastICA algorithm.Therefore,combining relevant attack behavior information,the attack separation conditions for mali-cious node are derived.The experimental results show that by distributing the test data according to a 1∶1 load standard,the designed system can effectively detect malicious node attack behavior,and the obtained real-time detection quantity value of ma-licious node has a fitting degree close to 100%with the rated value,which can better maintain the operational stability of the network system.

improved FastICA algorithmindustrial control networkmalicious nodeattack detectionnode identificationnode separation

江山杉

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成都中医药大学附属医院,四川,成都 610032

改进FastICA算法 工控网络 恶意节点 攻击检测 节点辨识 节点分离

四川省自然科学基金

2020SC09341

2024

微型电脑应用
上海市微型电脑应用学会

微型电脑应用

CSTPCD
影响因子:0.359
ISSN:1007-757X
年,卷(期):2024.40(9)