DIMY: Enabling privacy-preserving contact tracing.

Area of Science:

• Computer Science
• Cybersecurity
• Public Health

Background:

• The COVID-19 pandemic necessitated rapid spread reduction strategies, including digital contact tracing.
• Existing digital contact tracing apps face low adoption rates due to significant privacy and security concerns.
• Traditional manual contact tracing is labor-intensive and less scalable in widespread outbreaks.

Purpose of the Study:

• To introduce a novel blockchain-based protocol for privacy-preserving digital contact tracing.
• To address and mitigate privacy and security apprehensions associated with current contact tracing technologies.
• To develop a solution with efficient data handling and minimal resource overhead.

Main Methods:

• Implementation of a blockchain-based protocol named "Did I Meet You" (DIMY).
• Utilization of Bloom filters for efficient, privacy-preserving data storage.
• Employment of Diffie-Hellman key exchange for secure secret sharing among participants.

Main Results:

• DIMY ensures full-lifecycle data privacy protection on both client devices and back-end servers.
• The protocol demonstrates resilience against numerous known security attacks.
• DIMY exhibits significantly lower storage footprint on devices and servers compared to existing solutions.

Conclusions:

• The DIMY protocol effectively enhances privacy and security in digital contact tracing.
• Blockchain technology, combined with Bloom filters and Diffie-Hellman exchange, offers a viable solution to adoption barriers.
• DIMY presents a scalable and efficient alternative for public health initiatives requiring contact tracing.