Title: Key Management and Learning based Two Level Data Security for Metering Infrastructure of Smart Grid,
Abstract: In the smart grid, smart meters, and numerous control and monitoring
applications employ bidirectional wireless communication, where security is a
critical issue. In key management based encryption method for the smart grid,
the Trusted Third Party (TTP), and links between the smart meter and the third
party are assumed to be fully trusted and reliable. However, in wired/wireless
medium, a man-in-middle may want to interfere, monitor and control the network,
thus exposing its vulnerability. Acknowledging this, in this paper, we propose
a novel two level encryption method based on two partially trusted simple
servers (constitutes the TTP) which implement this method without increasing
packet overhead. One server is responsible for data encryption between the
meter and control center/central database, and the other server manages the
random sequence of data transmission. Numerical calculation shows that the
number of iterations required to decode a message is large which is quite
impractical. Furthermore, we introduce One-class support vector machine
(machine learning) algorithm for node-to-node authentication utilizing the
location information and the data transmission history (node identity, packet
size and frequency of transmission). This secures data communication privacy
without increasing the complexity of the conventional key management scheme.