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2014 | Book

Querying over Encrypted Data in Smart Grids

Authors: Mi Wen, Rongxing Lu, Xiaohui Liang, Jingsheng Lei, Xuemin (Sherman) Shen

Publisher: Springer International Publishing

Book Series : SpringerBriefs in Computer Science


About this book

This SpringerBrief presents the concept of the smart grid architecture and investigates the security issues of the smart grid and the existing encrypted data query techniques. Unique characteristics of smart grid impose distinguished challenges on this investigation, such as multidimensional attributes in metering data and finer grained query on each dimension. Three kinds of queries are introduced, namely, equality query, conjunctive query and range query. For the equality query over encrypted metering data, an efficient searchable encryption scheme is introduced and can be applied for auction in emerging smart grid marketing. Later chapters examine the conjunctive query and range query over encrypted data. Different techniques are used, including the Public key Encryption with Keyword Search (PEKS) and Hidden Vector Encryption (HVE), to construct the comparison predicate and range query predicate. Their correctness is demonstrated in the book. Concise and practical, Encrypted Data Querying in Smart Grids is valuable for professionals and researchers involved in data privacy or encryption. It is also useful for graduate students interested in smart grid and related technologies.

Table of Contents

Chapter 1. Introduction
Smart grid, envisioned as an indispensable power infrastructure, is featured by real-time and two-way communications. By installing smart meters at users’ houses, the smart grid can collect real-time data about power consumption by residential users. The amount of data generated by smart meters and intelligent sensors in smart grid will experience explosive growth in the next few years. According to a recent report from SBI Energy, the volume of smart grid data that will have to be managed by utilities is going to surge from 10,780 terabytes (TB) in 2010 to over 75,200 TB in 2015. How to query and mine this massive and heterogeneous power system raw data to support decision making and ensure reliability will be very critical for smart grid.
Mi Wen, Rongxing Lu, Xiaohui Liang, Jingsheng Lei, Xuemin (Sherman) Shen
Chapter 2. Equality Query for Auction in Emerging Smart Grid Marketing
Distributed energy resources (DERs), which are characterized by small scale power generation technologies to provide an enhancement of the traditional power system, have been strongly encouraged to be integrated into the smart grid, and numerous trading strategies have recently been proposed to support the energy auction in the emerging smart grid marketing. However, few of them consider the security aspects of energy trading, such as privacy-preservation, bid integrity and pre-filtering ability. In this chapter, we introduce an efficient Searchable Encryption Scheme for Auction (SESA) in emerging smart grid marketing. Specifically, SESA uses a public key encryption with keyword search technique to enable the energy sellers, e.g. DERs, to inquire suitable bids while preserving the privacy of the energy buyers (EBs). Additionally, to facilitate the seller to search for detailed information of the bids, we also propose an extension of SESA to support conjunctive keywords search.
Mi Wen, Rongxing Lu, Xiaohui Liang, Jingsheng Lei, Xuemin (Sherman) Shen
Chapter 3. Conjunctive Query over Encrypted Multidimensional Data
With the deployment of smart meters at individual households, smart grid can collect metering data of users’ power consumption. However, users’ power usage patterns would also be revealed. To preserve the users’ privacy, metering data is mostly encrypted by cryptographic algorithms. When data mining is needed to support decision making or ensure reliability, to find useful information from the encrypted data is very important for smart grid. Most of the traditional keyword searching schemes rarely consider both users’ data privacy and requesters’ query privacy. In particular, the power system data in smart grid has multidimensional attributes; thus, how to query over the encrypted multidimensional data on all dimensions is a challenging issue in smart grid. To achieve finer grained conjunctive query, this chapter introduces an Efficient Conjunctive Query (ECQ) scheme. Specifically, the ECQ incorporates the idea of public key encryption and conjunctive keywords search to achieve conjunctive query without data and query privacy leakage. Security analysis demonstrates that the ECQ can achieve the security requirements, namely, data confidentiality, integrity and privacy, as well as query privacy.
Mi Wen, Rongxing Lu, Xiaohui Liang, Jingsheng Lei, Xuemin (Sherman) Shen
Chapter 4. Range Query over Encrypted Metering Data for Financial Audit
Smart grid, envisioned as an indispensable power infrastructure, is featured by real-time and two-way communications. However, how to securely retrieve and audit the communicated metering data for validation testing is still challenging for smart grid. In this chapter, we introduce a novel privacy-preserving range query scheme over encrypted metering data, named PaRQ, to address the privacy issues in financial auditing for smart grid. The PaRQ allows a residential user to store metering data on a cloud server in an encrypted form. When financial auditing is needed, an authorized requester can send its range query tokens to the cloud server to retrieve the metering data. Specifically, the PaRQ constructs a hidden vector encryption (HVE) based range query predicate to encrypt the searchable attributes and session keys of the encrypted data. Meanwhile, the requester’s rang query can be transferred into two query tokens, which are used to find the matched query results.
Mi Wen, Rongxing Lu, Xiaohui Liang, Jingsheng Lei, Xuemin (Sherman) Shen
Chapter 5. Conclusions and Future Works
In this brief, we have investigated querying techniques in the smart grid. We conclude the brief with the following remarks.
Mi Wen, Rongxing Lu, Xiaohui Liang, Jingsheng Lei, Xuemin (Sherman) Shen
Querying over Encrypted Data in Smart Grids
Mi Wen
Rongxing Lu
Xiaohui Liang
Jingsheng Lei
Xuemin (Sherman) Shen
Copyright Year
Electronic ISBN
Print ISBN

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