Multimodal Transport : Secure Two-Party Computation in a Privacy-Preserving Android App

What is it about?

In recent times, safeguarding data privacy has become more crucial due to the rise in cyber threats and unauthorized sharing of sensitive data in every context. Our work aims to make sharing information in multimodal transport systems secure while respecting data privacy. Our contribution involves creating a safe way to share information, so we developed a system using Yao's garbled circuits, where two parties are involved, in an Android mobile environment. This system lets users locate points of interest like restaurants or hotels near specific places without revealing their personal details. The clever part is that the system matches user requests without exposing their preferences to external parties. We ensured the reliability of our project by following a threat model based on LINDDUN. This highlights the effectiveness of our approach. Moreover, it shows how secure computing methods can enable sharing information while upholding privacy.

Featured Image

Photo by Michał Parzuchowski on Unsplash

Photo by Michał Parzuchowski on Unsplash

Why is it important?

This work emphasizes the significance of giving priority to data privacy in today's interconnected world, especially in multimodal transport systems. The techniques we employed, such as secure two-party computing, show promise in achieving this objective. Besides, our framework is adaptable and can be used in various domains where data privacy is considered important. In conclusion, our efforts underscore the importance of data privacy and showcase the potential of secure two-party computing techniques in attaining this.

Perspectives