Abstract
Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can’t satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.
Highlights
To achieve dynamic charging capability, Advanced Metering Infrastructure uses Smart Meters (SM), two-way communication system, Home Area Network(HAN) and Metering Data Management System(MDMS) to establish communication links with users [1]
Intrusion detection evaluation from the performance point of view to verify the effectiveness of the intrusion detection method and feasibility of this article using the accuracy rate, false positive rate and false negative rate, training time and test time five indicators
Online Sequence Extreme Learning Machine (OS-Extreme Learning Machine (ELM)) method is equivalent to ELM method when the size of the selected block is as the same as the original training sample size, the accuracy and applicability of ELM, which is lower than OS-ELM
Summary
To achieve dynamic charging capability, Advanced Metering Infrastructure uses Smart Meters (SM), two-way communication system, Home Area Network(HAN) and Metering Data Management System(MDMS) to establish communication links with users [1]. The AMI is a complete network processing system that includes measure, collect, store, analyze and information utilizes the user’s power consumption, which provides the communication and control functions for the smart grid [20]. [29] presents a layered specification-based IDS for HAN in AMI, paper defines specifications that extract from the IEEE standard as the normal behavior and the specifications deviations from the normal behavior can be malicious activities and we use the machine learning method to learn the characteristics of attack data. Extreme Learning Machine (ELM) is a kind of generalized single hidden layer feedforward neural network (SLFNs) It uses the gradient-based learning algorithm to train the network, which is different from the traditional learning method and iteratively adjusting all parameters in the network.
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