A Framework to Optimize Geofence Privacy and Security

Open Access
- Author:
- Pi, Eileen
- Area of Honors:
- Cybersecurity Analytics & Operations
- Degree:
- Bachelor of Science
- Document Type:
- Thesis
- Thesis Supervisors:
- Anna Cinzia Squicciarini, Thesis Supervisor
Marc Aaron Friedenberg, Thesis Honors Advisor - Keywords:
- Geofence
Geofencing
Privacy
Security
Cybersecurity
Geolocation
Geospatial Intelligence
Location Obfuscation
Location-Based Service
LBS
GPS
Geofencing Obfuscation Algorithm
Geofencing Cybersecurity Framework - Abstract:
- Cellphones and smart devices are part of our lives and integrate seamlessly into our daily activities. Geolocation enabled applications are widely adopted and continue to increase in use and demand. Geofencing is a specialized geospatial intelligence tool that enables useful features in many applications, such as Google Maps, Uber, Covid-19 contact tracing, and Pokémon Go. The persistence of location reporting may place the privacy of users at an increased risk to reveal private personal information and movement trajectories based on location, time, and historical movement patterns. This research proposes a geofencing cybersecurity framework which offers a dynamic, quantitative, and scalable obfuscation algorithm supporting customizable levels of privacy based on person, time, and place. This geofencing cybersecurity framework overcomes the tradeoff between individual privacy and organizational security and offers the ability to harmonize and maximize both privacy and security. Using this geofencing obfuscation algorithm, individuals can increase their privacy while community and company can increase the security of their assets, mission, and values.