Privacy for location-based services
By: Ghinita, Gabriel.
Material type:
BookSeries: Synthesis digital library of engineering and computer science: ; Synthesis lectures on information security, privacy, and trust: # 4.Publisher: San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, c2013Description: 1 electronic text (xi, 73 p.) : ill., digital file.ISBN: 9781627051507 (electronic bk.).Subject(s): Location-based services -- Security measures | Mobile computing -- Access control | privacy | anonymity | security | homomorphic cryptography | PIR | differential privacy | spatial databases | GISDDC classification: 910.285 Online resources: Abstract with links to resource | Abstract with links to full text Also available in print.| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
E books
|
PK Kelkar Library, IIT Kanpur | Available | EBKE488 |
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
Part of: Synthesis digital library of engineering and computer science.
Series from website.
Includes bibliographical references (p. 67-71).
1. Introduction --
2. Privacy-preserving spatial transformations -- 2.1 Two-tier spatial transformations -- 2.2 Three-tier spatial transformations -- 2.3 Discussion --
3. Cryptographic approaches -- 3.1 A primer on computational PIR -- 3.2 Spatial queries with PIR -- 3.3 Protocols for approximate and exact NN with PIR -- 3.4 Comparison with geometric transformations --
4. Hybrid approaches -- 4.1 Privacy model -- 4.2 System overview -- 4.3 Private evaluation of point-rectangle enclosure -- 4.4 Private evaluation of point-convex-polygon enclosure --
5. Private matching of spatial datasets -- 5.1 Problem formulation -- 5.2 Dataset mapping -- 5.3 Join processing -- 5.4 Enhancing privacy by use of Chebyshev distance --
6. Trajectory anonymization -- 6.1 Publishing independent location samples -- 6.2 Publishing individual trajectories --
7. Differentially private publication of spatial datasets -- 7.1 A primer on differential privacy -- 7.2 Publication of static datasets of locations -- 7.2.1 Data-independent decompositions: quad-trees -- 7.2.2 Data-dependent decompositions: kd-trees -- 7.3 Publication of trajectory datasets --
8. Conclusions -- Bibliography -- Author's biography.
Abstract freely available; full-text restricted to subscribers or individual document purchasers.
Compendex
INSPEC
Google scholar
Google book search
Sharing of location data enables numerous exciting applications, such as location-based queries, location-based social recommendations, monitoring of traffic and air pollution levels, etc. Disclosing exact user locations raises serious privacy concerns, as locations may give away sensitive information about individuals' health status, alternative lifestyles, political and religious affiliations, etc. Preserving location privacy is an essential requirement towards the successful deployment of location-based applications. These lecture notes provide an overview of the state-of-the-art in location privacy protection. A diverse body of solutions is reviewed, including methods that use location generalization, cryptographic techniques or differential privacy. The most prominent results are discussed, and promising directions for future work are identified.
Also available in print.
Title from PDF t.p. (viewed on May 21, 2013).
There are no comments for this item.