Application of Secure Two-Party Computation in a Privacy-Preserving Android App
Marco De Vincenzi, Ilaria Matteucci, Fabio Martinelli, Stefano Sebastio · 2023
Data privacy has become increasingly important in recent years, with the rise of cyber threats and the unauthorized sharing of sensitive information. Our work within the E-Corridor project has focused on developing a secure framework for sharing information in multimodal transport systems, while ensuring data privacy is maintained. Our implementation of a two-party computation schema using Yao’s garbled circuits in an Android mobile setting has enabled us to create an application that allows users to find points of interest, e.g., restaurants or hotels, near specific areas without sharing any personal information. The application matches user requests using the secure two-party without disclosing any of the user’s preferences with external actors. We design a threat model based on LINDDUN to show the reliability of our project. It highlights also the potential of using secure computing techniques to enable information sharing while maintaining privacy. Our work demonstrates the importance of prioritizing data privacy in our increasingly interconnected world and the potential of secure two-party computing techniques in achieving this goal. Besides, this framework is flexible and can be extended to various domains where data privacy is of utmost importance.