Project Objective

The objective of the project CNS-1618391 is to systematically study the issue of anonymizing trajectory data, from the bottom layer of trajectory sensing and data collection, to the middle layer of trajectory representation and anonymity, to the application layer of how the anonymized trajectory data can be used. By the nature of trajectories as being time stamped sequence of points, in this project we develop novel geometric and topological algorithms for achieving the objective. Further we work in the setting in which the targets are being monitored by sensors placed in the environment. We plan to investigate distributed algorithms that have anonymity built in at the root when data is collected. Queries to such decentralized sensors are made to ensure no sensitive information is released.

Personnel

1. Professor Jie Gao (PI)
2. Dr. Chien Chun Ni (graduated August 2017)
3. Dr. Jiaxin Ding (graduated December 2018)
4. Haotian Wang (2018 - now)
5. Aria Rezaei (2017 - now)

Research Activities and Outputs

Talks

1. New Challenges in Distributed Sensing, Processing and Query of Spatial Data, invited talk at ALGO 2017.
2. New Challenges of Data Privacy in a Socially Connected World,

• Workshop of Computational Geometry & Machine Learning (Eindhoven, Netherlands), July 2018
• Shanghai Jiaotong University, June, 2018.
• Invited talk at the Fall Workshop on Computational Geometry, October 27th, 2018.
• Network Alignment and Anonymity, MobiHoc'19 TPC workshop, March 15th, 2019.
• Network Algorithms in an Increasingly Connected World, DIMACS REU Seminar Series, June 25, 2019.