School of Electronic Engineering and Computer Science

Privacy protection against spatial-temporal tracking

Supervisor: Dr Stefan Poslad

One of the main challenges for more widespread human use of IoT, which consists in part of more smart data sources and sinks that accompany humans when they move around, or are embedded in human environments, is data privacy for personal information acquired about individuals such as spatial-temporal tracks that perhaps detail our every movement. Increasingly, these tracks may not remain on a user’s mobile device where they could be protected via standard security mechanisms such as encryption but they need to be shared with location-based service providers and other third parties in order to access their services. Personal data privacy threats are that even if a pseudonym is used to identify a user’s actual identity, someone can be indirectly identified via their spatial-temporal data that is collected, i.e., via sensitive locations, e.g., where someone lives, and via someone’s spatial-temporal tracks being unique and repeatable. This project will investigate existing approaches to privacy protection against spatial-temporal tracking, and propose and validate new approaches.