Security and privacy preserving data aggregation in cloud computing

Abstract

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.

Achieving Data Dissemination with Security using FIWARE and Intel Software Guard Extensions (SGX)

“…Extensive experiments concluded that SGX adds a limited overhead providing much better performance when compared to other alternatives of Secure CBR. Silva et al [5] presents a solution for privacy and security preservation, also using Intel SGX and considering a smart metering application. Their experiments resulted in a relative low overhead.…”

“…To avoid such kind of attacks, the data can be encrypted in the producers in order to be processed only in a secure way. This can be achieved by homomorphic cryptography [5], which performs common operations over encrypted data, but its great overhead makes it unpractical to use with complex operations [6]. Another approach is the use of a trusted execution environment (TEE), that enables, by using specific hardware instructions, the creation of a shielded space in the memory in a way data can be processed securely inside this space.…”

“…Encrypted data enters the protected area, being decrypted only inside it and encrypted again before leaving. TEE use is more feasible than homomorphic cryptography, because, it takes considerably less time to process data [5]. Related to this problem, two research questions were identified for guiding this research: 1) How to limit the need to trust the storage provider and the consumer of the data?…”

DynSGX: A Privacy Preserving Toolset for Dinamically Loading Functions into Intel(R) SGX Enclaves

“…Possible applications of SGX have been discussed in [10], where examples of applications that make use of the SGX capabilities were presented, as well as an application architecture including an application split between components requiring security protection which should run within enclaves, and components that do not require protection and can therefore be executed outside enclaves. In [12], SGX is used for securely communicating and aggregating finegrained smart metering data in a cloud environment.…”

Secure and Privacy-Aware Data Dissemination for Cloud-Based Applications

“…Another proposal [24] makes use of Intel SGX technology to provide a simple solution for privacy-preserving smart metering system. The authors have suggested a model designed by trusted smart meter devices exchanging consumer's measurements with the trusted aggregator, performed inside an SGX enclave, among a secure channel established during the attestation process.…”