Advanced metering infrastructure( AMI) is a critical part of the smart grid,and ZigBee is playing an increasingly important role in AMI.The cyber security is the prerequisite to ensure the reliable operation of AMI.To...Advanced metering infrastructure( AMI) is a critical part of the smart grid,and ZigBee is playing an increasingly important role in AMI.The cyber security is the prerequisite to ensure the reliable operation of AMI.To guarantee the ZigBee communication security in AMI,a key management scheme based on the elliptic curve cryptosystem( ECC) is proposed.According to the ways of information transformation in AMI,the scheme is categorized as unicast communication key management process and multicast communication key management process.And in the scheme,the selection of elliptic curve,the calculation of ZigBee node's ECC public key and private key,the establishment and distribution of the link key in unicast communication,and the establishment and distribution of the network key in multicast communication are elaborated.The analysis results show that the proposed key management scheme is secure,and consumes less memory and energy,thus,can meet the demands of communication security of AMI.展开更多
An advanced metering infrastructure(AMI)system plays a key role in the smart grid(SG),but it is vulnerable to cyberattacks.Current detection methods for AMI cyberattacks mainly focus on the data center or a distribute...An advanced metering infrastructure(AMI)system plays a key role in the smart grid(SG),but it is vulnerable to cyberattacks.Current detection methods for AMI cyberattacks mainly focus on the data center or a distributed independent node.On one hand,it is difficult to train an excellent detection intrusion model on a self-learning independent node.On the other hand,large amounts of data are shared over the network and uploaded to a central node for training.These processes may compromise data privacy,cause communication delay,and incur high communication costs.With these limitations,we propose an intrusion detection method for AMI system based on federated learning(FL).The intrusion detection system is deployed in the data concentrators for training,and only its model parameters are communicated to the data center.Furthermore,the data center distributes the learning to each data concentrator through aggregation and weight assignments for collaborative learning.An optimized deep neural network(DNN)is exploited for this proposed method,and extensive experiments based on the NSL-KDD dataset are carried out.From the results,this proposed method improves detection performance and reduces computation costs,communication delays,and communication overheads while guaranteeing data privacy.展开更多
基金Sponsored by the National Natural Science Foundation of China(Grant No.51077015)the Fundamental Research Funds for the Central Universities(Grant No.HIT.NSRIF.2015017)
文摘Advanced metering infrastructure( AMI) is a critical part of the smart grid,and ZigBee is playing an increasingly important role in AMI.The cyber security is the prerequisite to ensure the reliable operation of AMI.To guarantee the ZigBee communication security in AMI,a key management scheme based on the elliptic curve cryptosystem( ECC) is proposed.According to the ways of information transformation in AMI,the scheme is categorized as unicast communication key management process and multicast communication key management process.And in the scheme,the selection of elliptic curve,the calculation of ZigBee node's ECC public key and private key,the establishment and distribution of the link key in unicast communication,and the establishment and distribution of the network key in multicast communication are elaborated.The analysis results show that the proposed key management scheme is secure,and consumes less memory and energy,thus,can meet the demands of communication security of AMI.
基金supported in part by the National Natural Science Foundation of China(No.51807013)the Foundation of Hunan Educational Committee(No.18B137)+1 种基金the Research Project in Hunan Province Education Department(No.21C0577)Postgraduate Research and Innovation Project of Hunan Province,China(No.CX20210791)。
文摘An advanced metering infrastructure(AMI)system plays a key role in the smart grid(SG),but it is vulnerable to cyberattacks.Current detection methods for AMI cyberattacks mainly focus on the data center or a distributed independent node.On one hand,it is difficult to train an excellent detection intrusion model on a self-learning independent node.On the other hand,large amounts of data are shared over the network and uploaded to a central node for training.These processes may compromise data privacy,cause communication delay,and incur high communication costs.With these limitations,we propose an intrusion detection method for AMI system based on federated learning(FL).The intrusion detection system is deployed in the data concentrators for training,and only its model parameters are communicated to the data center.Furthermore,the data center distributes the learning to each data concentrator through aggregation and weight assignments for collaborative learning.An optimized deep neural network(DNN)is exploited for this proposed method,and extensive experiments based on the NSL-KDD dataset are carried out.From the results,this proposed method improves detection performance and reduces computation costs,communication delays,and communication overheads while guaranteeing data privacy.
