Privacy-Preserving Contact Tracing Protocols

Abstract

Contact tracing is a critical tool in controlling infectious diseases by identifying and notifying individuals exposed to infected persons. The challenge lies in balancing public health benefits with individual privacy, particularly when using digital technologies. This paper reviews privacy-preserving contact tracing protocols—particularly those appearing in the early COVID-19 response—with an aim to outline key technologies, their advantages, limitations, and future research directions. Protocols such as DP-3T, BlueTrace, TCN Protocol, Trace-Σ, and Epione leverage cryptographic methods—like Temporary IDs, Bluetooth proximity tokens, Private Set Intersection (PSI), homomorphic encryption, zero-knowledge proofs, and k-anonymity techniques—to notify potential exposures without revealing identities or sensitive data. We analyze decentralized versus centralized designs, including Apple/Google Exposure Notification and PEPP-PT, exploring their trade-offs in privacy, scalability, and trust. Protocols are assessed based on their mechanisms, adoption feasibility, cryptographic resilience, and integration with public health infrastructure. Results highlight that decentralized approaches (e.g., DP-3T, TCN) offer stronger privacy guarantees by keeping contact logs on devices, while centralized models (like BlueTrace) allow human-in-the-loop validation but risk broader data exposure. Emerging proposals like Trace-Σ incorporate zero-knowledge proofs to allow anonymous graph construction. We discuss the methodological strengths and overheads of these schemes, including computational cost and reliance on user uptake. The paper concludes that while early protocols demonstrated feasibility and solid privacy foundations, challenges remain in adoption, interoperability, and governance. Future work should focus on enhanced cryptographic efficiency, formal privacy guarantees, decentralized governance, and empirical evaluation in diverse populations. The insights here lay groundwork for privacy-first contact tracing infrastructures adaptable beyond pandemic emergencies.