Privacy-friendly appliance load scheduling in smart grids

Abstract—The massive integration of renewable energy sources into the power grid ecosystem with the aim of reducing carbon emissions must cope with their intrinsically intermittent and unpredictable nature. Therefore, the grid must improve its capability of controlling the energy demand by adapting the power consumption curve to match the trend of green energy generation. This could be done by scheduling the activities of deferrable electrical appliances. However, communicating the users ’ needs about the usage of the electrical appliances leaks sensitive information about habits and lifestyles of the customers, thus arising privacy concerns. This paper proposes a privacy-preserving framework to allow the coordination of energy con-sumption without compromising the privacy of the users: the ser-vice requests generated by the domestic appliances are diveded in crypto-shares using Shamir Secret Sharing scheme and collected through an anonymous routing protocol based on Crowds by a set of schedulers, which schedule the requests operating directly on the shares. We discuss the security guarantees provided by our proposed infrastructure and evaluate its performance, comparing it with the optimal scheduling obtained through an Integer Linear Programming formulation. I

Privacy-preserving Cross-domain Routing Optimization -- A Cryptographic Approach

Today's large-scale enterprise networks, data center networks, and wide area networks can be decomposed into multiple administrative or geographical domains. Domains may be owned by different administrative units or organizations. Hence protecting domain information is an important concern. Existing general-purpose Secure Multi-Party Computation (SMPC) methods that preserves privacy for domains are extremely slow for cross-domain routing problems. In this paper we present PYCRO, a cryptographic protocol specifically designed for privacy-preserving cross-domain routing optimization in Software Defined Networking (SDN) environments. PYCRO provides two fundamental routing functions, policy-compliant shortest path computing and bandwidth allocation, while ensuring strong protection for the private information of domains. We rigorously prove the privacy guarantee of our protocol. We have implemented a prototype system that runs PYCRO on servers in a campus network. Experimental results using real ISP network topologies show that PYCRO is very efficient in computation and communication costs

A privacy-friendly gaming framework in smart electricity and water grids

Serious games can be used to push consumers of common-pool resources toward socially responsible consumption patterns. However, gamified interactions can result in privacy leaks and potential misuses of player-provided data. In the Smart Grid ecosystem, a smart metering framework providing some basic cryptographic primitives can enable the implementation of serious games in a privacy-friendly manner. This paper presents a smart metering architecture in which the users have access to their own high-frequency data and can use them as the input data to a multi-party secure protocol. Authenticity and correctness of the data are guaranteed by the usage of a public blockchain. The framework enables a gaming platform to administer a set of team game activities aimed at promoting a more sustainable usage of energy and water. We discuss and assess the performance of a protocol based on Shamir secret sharing scheme, which enables the members of the teams to calculate their overall consumption and to compare it with those of other teams without disclosing individual energy usage data. Additionally, the protocol impedes that the game platform learns the meter readings of the players (either individual or aggregated) and their challenge objectives

Secure equality testing protocols in the two-party setting

Protocols for securely testing the equality of two encrypted integers are common building blocks for a number of proposals in the literature that aim for privacy preservation. Being used repeatedly in many cryptographic protocols, designing efficient equality testing protocols is important in terms of computation and communication overhead. In this work, we consider a scenario with two parties where party A has two integers encrypted using an additively homomorphic scheme and party B has the decryption key. Party A would like to obtain an encrypted bit that shows whether the integers are equal or not but nothing more. We propose three secure equality testing protocols, which are more efficient in terms of communication, computation or both compared to the existing work. To support our claims, we present experimental results, which show that our protocols achieve up to 99% computation-wise improvement compared to the state-of-the-art protocols in a fair experimental set-up

Privacy-Preserving and Outsourced Multi-User k-Means Clustering

Many techniques for privacy-preserving data mining (PPDM) have been investigated over the past decade. Often, the entities involved in the data mining process are end-users or organizations with limited computing and storage resources. As a result, such entities may want to refrain from participating in the PPDM process. To overcome this issue and to take many other benefits of cloud computing, outsourcing PPDM tasks to the cloud environment has recently gained special attention. We consider the scenario where n entities outsource their databases (in encrypted format) to the cloud and ask the cloud to perform the clustering task on their combined data in a privacy-preserving manner. We term such a process as privacy-preserving and outsourced distributed clustering (PPODC). In this paper, we propose a novel and efficient solution to the PPODC problem based on k-means clustering algorithm. The main novelty of our solution lies in avoiding the secure division operations required in computing cluster centers altogether through an efficient transformation technique. Our solution builds the clusters securely in an iterative fashion and returns the final cluster centers to all entities when a pre-determined termination condition holds. The proposed solution protects data confidentiality of all the participating entities under the standard semi-honest model. To the best of our knowledge, ours is the first work to discuss and propose a comprehensive solution to the PPODC problem that incurs negligible cost on the participating entities. We theoretically estimate both the computation and communication costs of the proposed protocol and also demonstrate its practical value through experiments on a real dataset.Comment: 16 pages, 2 figures, 5 table

Transforming Secure Comparison Protocol from Passive to Active Adversary Model

Secure comparison (SC) is an essential primitive in Secure Multiparty Computation (SMC) and a fundamental building block in Privacy-Preserving Data Analytics. Although secure comparison has been studied since the introduction of SMC in the early 80s and many protocols have been proposed, there is still room for improvement, especially providing security against malicious adversaries who form the majority among the participating parties. It is not hard to develop an SC protocol secure against malicious majority based on the current state of the art SPDZ framework. SPDZ is design to work for arbitrary polynomially-bounded functionalities, and it may not provide the most efficient SMC implementation for a specific task, such as SC. In this paper, we propose a novel compiler that is specifically designed to convert most existing SC protocols with semi-honest security into the ones secure against the malicious majority. This compiler provides a flexible and efficient way to achieve both covert and active security for passively secure SC protocols

Multi Party Distributed Private Matching, Set Disjointness and Cardinality Set Intersection with Information Theoretic Security

In this paper, we focus on the specific problems of Private Matching, Set Disjointness and Cardinality Set Intersection in information theoretic settings. Specifically, we give perfectly secure protocols for the above problems in n party settings, tolerating a computational ly unbounded semi-honest adversary, who can passively corrupt at most t < n/2 parties. To the best of our knowledge, these are the first such information theoretically secure protocols in a multi-party setting for all three problems. Previous solutions for Distributed Private Matching and Cardinality Set Intersection were cryptographical ly secure and the previous Set Disjointness solution, though information theoretically secure, is in a two party setting. We also propose a new model for Distributed Private matching which is relevant in a multi-party setting