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In the smart grid, smart meters, and numerous control and monitoringapplications employ bidirectional wireless communication, where security is acritical issue. In key management based encryption method for the smart grid,the Trusted Third Party (TTP), and links between the smart meter and the thirdparty are assumed to be fully trusted and reliable. However, in wired/wirelessmedium, a man-in-middle may want to interfere, monitor and control the network,thus exposing its vulnerability. Acknowledging this, in this paper, we proposea novel two level encryption method based on two partially trusted simpleservers (constitutes the TTP) which implement this method without increasingpacket overhead. One server is responsible for data encryption between themeter and control center/central database, and the other server manages therandom sequence of data transmission. Numerical calculation shows that thenumber of iterations required to decode a message is large which is quiteimpractical. Furthermore, we introduce One-class support vector machine(machine learning) algorithm for node-to-node authentication utilizing thelocation information and the data transmission history (node identity, packetsize and frequency of transmission). This secures data communication privacywithout increasing the complexity of the conventional key management scheme.

Key Management and Learning based Two Level Data Security for Metering Infrastructure of Smart Grid