Measuring privacy in smart metering anonymized data

TL;DR

This paper evaluates the actual privacy level in anonymized smart meter data by using an entropy-based measure to assess how well overall consumption data prevents re-identification of fine-grained usage.

Contribution

It introduces an entropy-based metric to quantify privacy in anonymized smart metering data, considering the impact of overall consumption knowledge on re-identification risk.

Findings

Entropy measure quantifies privacy levels effectively.

Knowledge of total consumption reduces re-identification risk.

Provides insights into privacy guarantees of anonymization methods.

Abstract

In recent years, many proposals have arisen from research on privacy in smart metering. In one of the considered approaches, referred to as anonymization, smart meters transmit fine-grained electricity consumption values in such a way that the energy supplier can not exactly determine procedence. This paper measures the real privacy provided by such approach by taking into account that at the end of a billing period the energy supplier collects the overall electricity consumption of each meter for billing purposes. An entropy-based measure is proposed for quantifying privacy and determine the extent to which knowledge on the overall consumption of meters allows to re-identify anonymous fine-grained consumption values.