Privacy preserving in location based services

1. HCMC University of Technology Information System Security Course Privacy preserving in location based services Presenter: Nguyen Ba Anh

2. Content 1. Location-based service concepts 2. Preserving Privacy in Location-based Mobile Social Applications 2.1. Introduction 2.2. Motivating applications 2.3. Goals, system and threat model 2.4. Building blocks and their usage 2.5. Privacy analysis and tradeoffs

3. Content 3. Privacy-Preserving Techniques for Location-based Services 3.1. Problems 3.2. Two main approach 3.3. PROBE (Privacy-preserving Obfuscation Environment) 3.4. Private information retrieval (PIR) techniques 3.5. Privacy in some kind of LBS 4. Conclusion

4. 1. Location-based service concepts

5. 1.1. Location-based service (LBS) • Ageneral class of computer program-level services used to include specific controls for location and time data as control features in computer programs (Wikipedia)

6. 1.2. Types of LBS

7. 1.3. LBS statistic • Users • Usages

8. 1.4. Privacy issue

9. 2. Preserving Privacy in Location-based Mobile Social Applications

10. 2.1. Introduction • Wide-spread adoption (tremendous penetration) • Empower users with knowledge of their vicinity • Numerous untrusted servers offering different services • Proposed design: simple encrypted data store & move the application functionality to client smartphones.

11. 2.2. Motivating applications • Collaborative Content Downloading • Social Recommendations • Local Businesses • Locations-Based Reminders • Friend Locator

12. 2.3. GOALS, SYSTEM AND THREAT MODEL • System model: • iPhone 3G comes with a 412MHz processor and 512MB of RAM • Smartphones decrypt and consume friends’ data, the server stores users’ data, backs them up, and serve data to users

13. 2.3. GOALS, SYSTEM AND THREAT MODEL • Threat model: • third-party storage server is untrusted • user privacy lost even when the data stored on the server is leaked to an attacker

14. 2.4. BUILDING BLOCKS AND THEIR USAGE • Friendship Proof: • a cryptographic attestation A -> B using symmetric key • Users stores all their proofs from their friends • Communicate via a wireless interface and exchange using a cryptographically secure handshake

15. 2.4. BUILDING BLOCKS AND THEIR USAGE • Transaction Proof: • cryptographically attests that a piece of information belongs to a user • Include message for friends (current location, opinion, something helpful) • message is application-dependent, encrypted with the user’s session key when it is stored on the storage server

16. 2.4. BUILDING BLOCKS AND THEIR USAGE • Interfaces Exposed by the Storage Server

17. 2.5. PRIVACY ANALYSIS AND TRADEOFFS • Server Interface Privacy and Tradeoffs • Only the friend users with appropriate keys can decrypt the data • improve the performance by tagging each proof stored via a putLocationInfo call with an Id (or public key) of the user that generated the proof • achieve both performance and privacy in this call is to tag the proofs with an userId that changes periodically in a known pattern (known only to friends)

18. 2.5. PRIVACY ANALYSIS AND TRADEOFFS • Impact of Several Potential Attacks • A compromised client can leak the location privacy of all her friends • Compromised Third-party Storage Server (Stronger Threat Model) • DoS Attacks on the Server

19. 3. Privacy-Preserving Techniques for Location-based Services

20. 3.1. Problems • Location information is critical for providing customized services, on the other hand, can lead to privacy breaches • attacker may infer sensitive information about the individual by cross-referencing location information about an individual with other information and by exploiting domain knowledge

21. 3.2. Two main approaches • Location obfuscation

22. 3.2. Two main approaches • k-anonymization

23. 3.3. PROBE (Privacy-preserving Obfuscation Environment) • Based on key elements • The 1st element: sensitive entities and unreachable entities • The 2nd element: personal profile • The 3rd element: probabilistic privacy model • preferences are recorded in the individual personal profile

24. 3.4. Privateinformation retrieval (PIR) techniques • does not require intermediate parties to generate cloaked regions nor the presence of other individuals to achieve anonymity • may be quite expensive

25. 3.5. Privacy in some kind of LBS Privacy in Location-aware LBS

26. 3.5. Privacy in some kind of LBS Privacy in Location-aware LBS

27. 3.5. Privacy in some kind of LBS Privacy in Real-time LBS

28. 3.5. Privacy in some kind of LBS Privacy and Location Anonymization in LBS

29. 4. Conclusion • LBS present an important parts in the development of human • Customers, regulators and legislators all have an interest in privacy • Privacy can and should be designed into systems by minimizing personal data collection, storage

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