摘要
为提高工业无线传感器网络的入侵检测的精度和降低检测能耗,设计了基于属性变化率的全局信任入侵检测算法。通过属性变化率获取节点的全局信任值以检测攻击;通过人工蜂群算法选择最优簇头集以确保簇头的高可信度和降低网络整体的能耗;通过信任恢复机制恢复临时故障节点的信任,以降低虚警率。实验证明本方案具有较高的检测率和较低的虚警率,并能延长网络的生命周期。
In order to improve the accuracy and reduce the energy consumption of intrusion detection in industrial wireless sensor networks,a global trust intrusion detection algorithm based on attribute change rate is designed.The global trust value of the node is obtained through the attribute change rate to detect the attack.The optimal cluster head set is selected by using artificial bee colony algorithm to ensure the high reliability of cluster head and reduce the energy consumption of the whole network.The trust of the temporarily failed node is restored through the trust recovery mechanism to reduce the false alarm rate.Experiments show that this scheme has high detection rate and low false alarm rate,and can prolong the life cycle of the network.
作者
李创
孙子文
LI Chuang;SUN Ziwen(School of Internet of Things Engineering,Jiangnan University,Wuxi Jiangsu 214122,China;MOE Engineering Research Center of Internet of Things Technology Applications,Wuxi Jiangsu 214122,China)
出处
《传感技术学报》
CAS
CSCD
北大核心
2023年第2期294-300,共7页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金项目(61373126)
中央高校基本科研业务费专项资金项目(JUSRP51510)
江苏省自然科学基金项目(BK20131107)。
关键词
工业无线传感器网络
入侵检测
人工蜂群算法
全局信任
信任恢复
industrial wireless sensor networks
intrusion detection
artificial bee colony
global trust
trust recovery
