A Study into Smart Grid Consumer-User Profiling for Security Applications

A smart meter measures energy consumption with more granular detail than conventional analogue meters. The Advanced Metering Infrastructure (AMI) facilitates real-time two-way communication between the consumer and the rest of the energy grid. Information concerning electricity consumption, demand and response and home energy generation is communicated back to the local utility for monitoring and billing purposes. However, the detailed electricity usage patterns and trends can also be used to understand daily consumer habits and their routines. The collection and analysis of such data raises significant security and ethical concerns which must be adequately addressed. This paper focuses on the data collected from the residential smart grid using its default reading frequency of 30 minutes. The research demonstrates how the information can be exploited to remotely profile users and detect abnormal user behaviours using cloud-based analytics. Security implications are outlined and a case study is put forward as a demonstration of information that can be obtained through consumer profiling