Smart Grid Communication Infrastructures

9A Secure Data Learning Scheme for Big Data Applications in the Smart Grid

In this chapter, a secure data learning scheme is proposed for big data applications in the information and communication technology infrastructure of the smart grid. The proposed scheme allows multiple parties to find the predictive models from their overall data, while not revealing their own private data to one another at the same time. Instead of deploying a centralized data learning process, the scheme distributes data learning tasks to the local learning parties as their own local data learning tasks to learn the value from local data, thus preserving privacy. In addition, an associated secure scheme is proposed to guarantee the privacy of learning results during the information reassembly and value‐response process. An evaluation is performed to verify the privacy of the training data set, as well as the accuracy of learning weights. A case study is presented based on an open metering data analysis.

9.1 Background and Related Work

9.1.1 Motivation and Background

Nowadays, information and communication technology (ICT) infrastructure has been able by modern control techniques to tremendously improve the efficiency, reliability, and security of information systems [145]. Big data is an emerging topic due to its various applications [146]. However, it would not be so prevalent without the underlying support of the ICT, due to its extremely large volume of data and computing complexity. When a huge volume ...