Enhancing the Utility of Privacy-Preserving Techniques in Location-based Services (LBS) Applications

PhD Thesis Proposal Defence


Title: "Enhancing the Utility of Privacy-Preserving Techniques in 
Location-based Services (LBS) Applications"

by

Mr. Maocheng LI


Abstract:

The widespread use of GPS-enabled devices has led to the proliferation of 
spatial data (e.g., locations, trajectories), enabling applications like 
ride-hailing and contact tracing. However, sharing such data raises 
significant privacy concerns, as sensitive information -- such as personal 
habits or health conditions -- can be inferred from spatial patterns. While 
Differential Privacy (DP) provides rigorous theoretical guarantees for 
privacy preservation, its noise-injection mechanisms often degrade data 
utility, limiting the accuracy of location-based services (LBS). Thus, there 
is an urgent need for privacy-preserving techniques that maintain data 
utility.

This thesis proposal addresses this challenge by developing novel frameworks 
that integrate DP with Secure Multiparty Computation (SMC) across three 
critical applications: (1) spatial crowdsourcing, where we propose k-Switch, 
which achieves 37% improvement in task assignment success rates compared to 
the baseline; (2) contact tracing, where we introduce ContactGuard, which 
accelerates SMC operations using Geo-I-perturbed trajectories, maintaining 
98% recall in identifying close contacts; and (3) spatial federation, where 
we develop FedGroup, which reduces the aggregate Laplace noise by 72% 
compared to other standard DP baselines.

We demonstrate that our frameworks achieve provable privacy guarantees 
(satisfying epsilon-differential privacy or its variants) while 
significantly improving the utility and efficiency over state-of-the-art 
methods, verified by extensive experiments. The thesis proposal concludes 
with open challenges and future directions.


Date:                   Friday, 23 May 2025

Time:                   2:00pm - 4:00pm

Venue:                  Room 2128A
                        Lift 19

Committee Members:      Prof. Lei Chen (Supervisor)
                        Prof. Ke Yi (Chairperson)
                        Prof. Cunsheng Ding