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Querying over Encrypted Data in Smart Grids [Pehme köide]

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  • Formaat: Paperback / softback, 78 pages, kõrgus x laius: 235x155 mm, kaal: 1474 g, 17 Illustrations, color; 5 Illustrations, black and white; IX, 78 p. 22 illus., 17 illus. in color., 1 Paperback / softback
  • Sari: SpringerBriefs in Computer Science
  • Ilmumisaeg: 21-May-2014
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319063545
  • ISBN-13: 9783319063546
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Querying over Encrypted Data in Smart GridsSuurem pilt
  • Formaat: Paperback / softback, 78 pages, kõrgus x laius: 235x155 mm, kaal: 1474 g, 17 Illustrations, color; 5 Illustrations, black and white; IX, 78 p. 22 illus., 17 illus. in color., 1 Paperback / softback
  • Sari: SpringerBriefs in Computer Science
  • Ilmumisaeg: 21-May-2014
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319063545
  • ISBN-13: 9783319063546
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783319063546.html
Märksõnad:
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.

Arvustused

The booklet under review is a comprehensive study that investigates the problem of querying encrypted data in smart grids and focuses on preserving data and query privacy, a topic that is rarely discussed, but is nevertheless of great importance. the booklet is a self-contained and interesting study that can be used as a reference point in the domain for documentation and future research in the area. (Adrian Atanasiu, zbMATH 1308.68012, 2015)

1 Introduction
1(18)
1.1 Smart Grid Architecture
1(3)
1.1.1 Power System Layer
3(1)
1.1.2 Communications Layer
3(1)
1.2 Security Challenges in SGCN
4(5)
1.2.1 Security Objectives in SGCN
5(1)
1.2.2 Attacks in SGCN
5(2)
1.2.3 Coutermeasures in SGCN
7(2)
1.3 Existing Techniques for Encrypted Data Query
9(3)
1.3.1 Order-Preserving Encryption
10(1)
1.3.2 Searchable Encryption Techniques
10(1)
1.3.3 Special Data Structure Traversal
11(1)
1.3.4 Data Partitioning Problems
11(1)
1.4 Security Primitives
12(7)
1.4.1 Bilinear Pairing
12(1)
1.4.2 PKE with Keyword Search
12(1)
1.4.3 HEV Based Query Predicate
13(2)
References
15(4)
2 Equality Query for Auction in Emerging Smart Grid Marketing
19(18)
2.1 Introduction
19(1)
2.2 System Model and Design Goal
20(3)
2.2.1 Smart Grid Marketing Architecture
21(1)
2.2.2 Security Requirements
22(1)
2.2.3 Design Goal
22(1)
2.3 SESA Scheme
23(2)
2.3.1 Registration Phase
23(1)
2.3.2 Bidding Phase
24(1)
2.3.3 Pre-filtering Phase
24(1)
2.3.4 Decision-of-Winner Phase
25(1)
2.4 Extended SESA with Conjunctive Keywords Search
25(3)
2.4.1 Registration Phase
25(1)
2.4.2 Information Encryption
26(1)
2.4.3 Pre-filtering Phase
27(1)
2.5 Security Analysis
28(1)
2.6 Performance Analysis
29(4)
2.6.1 SESA vs. EPPKS
29(2)
2.6.2 Extended SESA vs. EPPKS
31(2)
2.7 Related Works
33(1)
2.8 Summary
34(3)
References
34(3)
3 Conjunctive Query over Encrypted Multidimensional Data
37(14)
3.1 Introduction
37(1)
3.2 System Model, Security Requirements and Design Goal
38(3)
3.2.1 System Model
39(1)
3.2.2 Security Requirements
39(1)
3.2.3 Design Goal
40(1)
3.3 The ECQ Scheme
41(3)
3.3.1 Registration Phase
41(1)
3.3.2 Data and Tags Encryption Phase
41(1)
3.3.3 Conjunctive Query Phase
42(1)
3.3.4 Data Recovery Phase
43(1)
3.4 Performance Analysis
44(4)
3.4.1 Security Analysis
44(1)
3.4.2 Performance Evaluation
45(3)
3.5 Related Works
48(1)
3.6 Summary
49(2)
References
50(1)
4 Range Query over Encrypted Metering Data for Financial Audit
51(26)
4.1 Introduction
51(2)
4.2 System Model, Security Requirements and Design Goal
53(3)
4.2.1 System Model
53(1)
4.2.2 Security Requirements
54(1)
4.2.3 Designing Goal
55(1)
4.3 The PaRQ Scheme
56(7)
4.3.1 Construction of the Range Query Predicate
56(1)
4.3.2 The Encrypted Data Deposit Phase
57(3)
4.3.3 Range Query Phase
60(3)
4.3.4 Enhancement with Collusion Resilience
63(1)
4.4 Security Analysis
63(3)
4.5 Performance Evaluation
66(6)
4.5.1 Communication Overhead
66(2)
4.5.2 Computation Overhead
68(1)
4.5.3 Response Time
69(3)
4.6 Related Works
72(2)
4.6.1 Security and Privacy in Smart Grid
72(1)
4.6.2 Range Query
73(1)
4.7 Summary
74(3)
References
74(3)
5 Conclusions and Future Works
77
5.1 Conclusions
77(1)
5.2 Future Research Directions
78