Privacy and anonymization for G-LocON

The Geographical Location Oriented Network (G-LocON), developed at Shibaura Institute of Technology, is a hybrid peer-to-peer (P2P) system that enables geo-location-oriented device-to-device communication through the use of existing technologies such as Long Term Evolution (LTE), Wireless Fidelity (Wi-Fi), and Bluetooth. G-LocON incorporates a location tracker, which maintains the Location Information (LI) of user devices and facilitates the discovery of adjacent devices, thereby reducing the amount of data transport compared to client/server models and minimizing the risk of a loss of connection to other devices in the event of a central server failure.

To ensure the readiness of G-LocON for real-world applications, it was necessary to assess the current state of the framework and address any security issues. As part of this project, I conducted research on how personal data within G-LocON could be anonymized while adhering to the General Data Protection Regulation (GDPR) and other privacy laws. To gather additional insights and ideas on anonymization, I organized a security hackathon, resulting in the identification of 30 security and privacy requirements, which were plotted on a dashboard to aid future researchers in understanding the most crucial elements for achieving GDPR compliance. Prototypes of improved anonymization were also developed, along with a functional and technical design.

The research findings indicated that personal data within G-LocON could be anonymized by randomizing the unique identifier of peers using the network and hiding location information by default. Multiple measures were implemented to ensure compliance with the GDPR, such as the implementation of permanent storage to demonstrate the granting of permission to process personal data. This research prepared G-LocON for future development by conducting a compliance assessment of the current framework and providing recommendations on improvements to meet GDPR requirements.