Preserving privacy against side-channel leaks : from data publishing to web applications /: from data publishing to web applications. (2016)
- Record Type:
- Book
- Title:
- Preserving privacy against side-channel leaks : from data publishing to web applications /: from data publishing to web applications. (2016)
- Main Title:
- Preserving privacy against side-channel leaks : from data publishing to web applications
- Further Information:
- Note: Wen Ming Liu, Lingyu Wang.
- Authors:
- Liu, Wenming
Wang, Lingyu - Contents:
- Preface; Acknowledgments; Contents; 1 Introduction; 1.1 Background; 1.2 Overview; 1.3 Summary of Contributions; References; 2 Related Work; 2.1 Privacy Preservation; 2.2 Side-Channel Attacks; 2.3 Side-Channel Leaks in Data Publishing; 2.4 Side-Channel Leaks in Web Applications; 2.5 Side-Channel Leaks in Smart Metering; References; 3 Data Publishing: Trading Off Privacy with Utility Through the k-Jump Strategy; 3.1 Overview; 3.2 The Model; 3.2.1 The Algorithms anaive and asafe; 3.3 k-Jump Strategy; 3.3.1 The Algorithm Family ajump(k k k k); 3.3.2 Properties of ajump(k k k k). 3.4 Data Utility Comparison3.4.1 Data Utility of k-Jump Algorithms; 3.4.1.1 The Case of ajump(1) vs. ajump(i) (i>1); 3.4.1.2 The Case of ajump(i) vs. ajump(j) (1<i<j); 3.4.1.3 The Case of ajump(k1 k1 k1 k1) vs. ajump(k2 k2 k2 k2) (k1 k1 k1 k1 k2 k2 k2 k2); 3.4.2 Reusing Generalization Functions; 3.4.3 The Relationships of asafe and ajump(1); 3.5 Computational Complexity; 3.6 Making Secret Choices of Algorithms; 3.6.1 Secret-Choice Strategy; 3.6.2 Subset Approach; 3.7 Summary; References; 4 Data Publishing: A Two-Stage Approach to Improving Algorithm Efficiency; 4.1 Overview. 4.1.1 Motivating Example4.2 The Model; 4.2.1 The Basic Model; 4.2.2 l-Candidate and Self-Contained Property; 4.2.3 Main Results; 4.3 The Algorithms; 4.3.1 The RIA Algorithm (Random and Independent); 4.3.2 The RDA Algorithm (Random and Dependent); 4.3.3 The GDA Algorithm (Guided and Dependent); 4.3.4 The Construction of SGSS; 4.4Preface; Acknowledgments; Contents; 1 Introduction; 1.1 Background; 1.2 Overview; 1.3 Summary of Contributions; References; 2 Related Work; 2.1 Privacy Preservation; 2.2 Side-Channel Attacks; 2.3 Side-Channel Leaks in Data Publishing; 2.4 Side-Channel Leaks in Web Applications; 2.5 Side-Channel Leaks in Smart Metering; References; 3 Data Publishing: Trading Off Privacy with Utility Through the k-Jump Strategy; 3.1 Overview; 3.2 The Model; 3.2.1 The Algorithms anaive and asafe; 3.3 k-Jump Strategy; 3.3.1 The Algorithm Family ajump(k k k k); 3.3.2 Properties of ajump(k k k k). 3.4 Data Utility Comparison3.4.1 Data Utility of k-Jump Algorithms; 3.4.1.1 The Case of ajump(1) vs. ajump(i) (i>1); 3.4.1.2 The Case of ajump(i) vs. ajump(j) (1<i<j); 3.4.1.3 The Case of ajump(k1 k1 k1 k1) vs. ajump(k2 k2 k2 k2) (k1 k1 k1 k1 k2 k2 k2 k2); 3.4.2 Reusing Generalization Functions; 3.4.3 The Relationships of asafe and ajump(1); 3.5 Computational Complexity; 3.6 Making Secret Choices of Algorithms; 3.6.1 Secret-Choice Strategy; 3.6.2 Subset Approach; 3.7 Summary; References; 4 Data Publishing: A Two-Stage Approach to Improving Algorithm Efficiency; 4.1 Overview. 4.1.1 Motivating Example4.2 The Model; 4.2.1 The Basic Model; 4.2.2 l-Candidate and Self-Contained Property; 4.2.3 Main Results; 4.3 The Algorithms; 4.3.1 The RIA Algorithm (Random and Independent); 4.3.2 The RDA Algorithm (Random and Dependent); 4.3.3 The GDA Algorithm (Guided and Dependent); 4.3.4 The Construction of SGSS; 4.4 Experiments; 4.4.1 Computation Overhead; 4.4.2 Data Utility; 4.5 Discussion; 4.6 Summary; References; 5 Web Applications: k-Indistinguishable Traffic Padding; 5.1 Overview; 5.2 The Model; 5.2.1 Basic Model; 5.2.2 Privacy and Cost Model; 5.3 PPTP Problem Formulation. 5.3.1 SVSD and SVMD5.3.2 MVMD; 5.4 The Algorithms; 5.5 Extension to l-Diversity; 5.5.1 The Model and Problem Formulation; 5.5.2 The Algorithms; 5.6 Evaluation; 5.6.1 Implementation and Experimental Settings; 5.6.2 Communication Overhead; 5.6.3 Computational Overhead; 5.6.4 Processing Overhead; 5.7 Summary; References; 6 Web Applications: Background-Knowledge Resistant Random Padding; 6.1 Overview; 6.1.1 Motivating Example; 6.2 The Model; 6.2.1 Traffic Padding; 6.2.2 Privacy Properties; 6.2.3 Padding Method; 6.2.4 Cost Metrics; 6.3 The Algorithms; 6.3.1 The Random Ceiling Padding Scheme. 6.3.2 Instantiations of the Scheme6.4 The Analysis; 6.4.1 Analysis of Privacy Preservation; 6.4.2 Analysis of Costs; 6.4.3 Analysis of Computational Complexity; 6.5 Experiment; 6.5.1 Experimental Setting; 6.5.2 Uncertainty and Cost vs k; 6.5.3 Randomness Drawn from Bounded Uniform Distribution; 6.5.4 Randomness Drawn from Normal Distribution; 6.6 Summary; References; 7 Smart Metering: Inferences of Appliance Status from Fine-Grained Readings; 7.1 Overview; 7.2 Motivating Example; 7.3 The Model; 7.3.1 Adversary Model; 7.3.2 Privacy Property; 7.3.3 Cost Metrics; 7.4 Summary; References. … (more)
- Publisher Details:
- Switzerland : Springer
- Publication Date:
- 2016
- Extent:
- 1 online resource
- Subjects:
- 005.8
004
Computer science
Computer security
Internet -- Security measures
COMPUTERS -- Security -- General
Computer security
Internet -- Security measures
Computers -- Online Services -- General
Computers -- Hardware -- Network Hardware
Coding theory & cryptology
Computer networking & communications
Network hardware
Data encryption (Computer science)
Information systems
Computer Communication Networks
Computer security
Electronic books - Languages:
- English
- ISBNs:
- 9783319426440
3319426443 - Related ISBNs:
- 9783319426426
3319426427 - Notes:
- Note: Includes bibliographical references.
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- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
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- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.370291
- Ingest File:
- 02_350.xml