Security and Privacy Preserving Data Aggregation in Cloud Computing

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

An Electric Vehicle Charging Management Scheme Based on Publish/Subscribe Communication Framework

Motivated by alleviating CO$_2$ pollution, Electric Vehicle (EV) based applications have recently received wide interests from both commercial and research communities by using electric energy instead of traditional fuel energy. Although EVs are inherently with limited travelling distance, such limitation could be overcome by deploying public Charging Stations (CSs) to recharge EVs battery during their journeys. In this paper we propose a novel communication framework for on-the-move EV charging scenario, based on the Publish/Subscribe (P/S) mechanism for disseminating necessary CS information to EVs, in order for them to make optimized decisions on where to charge. A core part of our communication framework is the utilization of Road Side Units (RSUs) to bridge the information flow from CSs to EVs, which has been regarded as a type of cost-efficient communication infrastructure. Under this design, we introduce two complementary communication modes of signalling protocols, namely Push and Pull Modes, in order to enable the required information dissemination operation. Both analysis and simulation show the advantage of Pull Mode, in which the information is cached at RSUs to support asynchronous communication. We further propose a remote reservation service based on the Pull Mode, such that the CS-selection decision making can utilize the knowledge of EVs' charging reservation, as published from EVs through RSUs to CSs. Results show that both the performance at CS and EV sides are further improved based on using this anticipated information.Comment: IEEE Systems Journal 201

Distributed Event-Triggered Algorithms for Finite-Time Privacy-Preserving Quantized Average Consensus

In this paper, we consider the problem of privacy preservation in the average consensus problem when communication among nodes is quantized. More specifically, we consider a setting where some nodes in the network are curious but not malicious and they try to identify the initial states of other nodes based on the data they receive during their operation (without interfering in the computation in any other way), while some nodes in the network want to ensure that their initial states cannot be inferred exactly by the curious nodes. We propose two privacy-preserving event-triggered quantized average consensus algorithms that can be followed by any node wishing to maintain its privacy and not reveal the initial state it contributes to the average computation. Every node in the network (including the curious nodes) is allowed to execute a privacy-preserving algorithm or its underlying average consensus algorithm. Under certain topological conditions, both algorithms allow the nodes who adopt privacypreserving protocols to preserve the privacy of their initial quantized states and at the same time to obtain, after a finite number of steps, the exact average of the initial states.Comment: 12 page