Anonymity Framework Project

Project II: Anonymity Framework

Preserving Anonymity of Context-aware Location-based Services

Privacy has become an important goal in designing location-based services. Service providers want to verify legitimate users and allow permitted users to enjoy their services. Users, however, want to preserve their privacy from being tracked. In this project, a new framework providing users with more privacy and anonymity in both authentication and querying process is proposed. Unlike the existing works, our framework benefits from a combination of three important techniques: k-anonymity, timed-fuzzy logic and one-way hash function. Using these existing schemes with some adding and adaptation, it gives us simpler solution, less complexity, and yet maturity. During authentication, the one-way hash function provides users with more privacy by using fingerprints of users’ identities. To provide anonymous authentication, the concept of confidence level is adopted with timed-fuzzy logic. Regarding location privacy, spatial k-anonymity prevents the users’ location from being tracked. The proposed framework is expected to strengthen anonymity and privacy to a user by consuming a small extra implementation cost, in addition to functionality improvement.

Outputs
– Framework for preserving anonymity of context-aware location-based services
– Published paper

Possible partners so far:
NECTEC (Thailand)
De La Salle University (The Philippines)
BAY Zoltan (Hungary)