A secure location-based alert system with tunable privacy-performance trade-off.

Area of Science:

• Computer Science
• Cryptography
• Mobile Computing

Background:

• Monitoring mobile user location updates has vital applications in public health, national security, and advertising.
• Protecting user privacy is crucial due to sensitive information derivable from movement patterns.
• Searchable encryption enables conditional location disclosure but often relies on computationally expensive pairing-based cryptography (PBC).

Purpose of the Study:

• To propose secure and efficient techniques for private processing of location updates.
• To enhance the performance of searchable encryption for location-based services.
• To reduce the reliance on expensive pairing operations in cryptographic privacy solutions.

Main Methods:

• Developed techniques to complement pairing-based cryptography (PBC) for location updates.
• Implemented optimizations including result materialization and parallelization.
• Introduced a heuristic to enlarge alert zones, trading controlled privacy for performance gains.

Main Results:

• Proposed techniques significantly improve performance compared to baseline methods.
• Reduced the overhead of searchable encryption to practical levels for cloud computing.
• Experimental results demonstrate substantial performance gains and efficiency improvements.

Conclusions:

• The developed techniques make private location update processing practical and efficient.
• Optimizations and heuristics effectively reduce computational overhead.
• This work enables wider adoption of privacy-preserving location-based services.