Recommender System for Privacy-Preserving Solutions in Smart Metering

Nowadays, Smart Grid is envisaged to provide several benefits to both customers and grid operators, due to the bi-directional communication that allows better control over energy usage. However, Smart Meters (SM) introduce many privacy issues if consumption data is analysed, being possible to draw accurate conclusions about customers' private life. In this paper we analyse the main techniques that address privacy when collecting electricity readings, classifying such solutions into various criteria, ranging from their architecture to its implemented cryptosystem. In addition to privacy, it is equally important to preserve efficiency to carry on with monitoring operations, so further control requirements are also studied. Our aim is to provide guidance to installers who intend to integrate such mechanisms on the grid, according to their needs and available equipment. To do so, we present an expert system based on a Bayesian network to recommend an appropriate deployment strategy.