CRFeb 14, 2019

Security and Privacy Preserving Data Aggregation in Cloud Computing

arXiv:1902.05334v118 citations
Originality Synthesis-oriented
AI Analysis

This addresses privacy concerns for residential customers in smart grids, but it is incremental as it applies existing SGX technology to a known problem.

The paper tackled the privacy threats in smart metering for smart grids by using Intel SGX technology to provide a solution that meets all privacy requirements, with experiments comparing its performance to a non-private implementation.

Smart metering is an essential feature of smart grids, allowing residential customers to monitor and reduce electricity costs. Devices called smart meters allows residential customers to monitor and reduce electricity costs, promoting energy saving, demand management, and energy efficiency. However, monitoring a households' energy consumption through smart meters poses serious privacy threats, and have thus become a major privacy issue. Hence, a significant amount of research has appeared recently with the purpose of providing methods and mechanisms to reconcile smart metering technologies and privacy requirements. However, most current approaches fall short in meeting one of several of the requirements for privacy preserving smart metering systems. In this paper we show how Intel SGX technology can be used to provide a simple and general solution for the smart metering privacy problem that meets all these requirements in a satisfactory way. Moreover, we present also an implementation of the proposed architecture as well as a series of experiments that have been carried out in order to assess how the proposed solution performs in comparison to a second implementation of the architecture that completely disregards privacy issues.

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