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Contact tracing is an important measure to counter the COVID-19 pandemic. Inthe early phase, many countries employed manual contact tracing to contain therate of disease spread, however it has many issues. The manual approach iscumbersome, time consuming and also requires active participation of a largenumber of people to realize it. In order to overcome these drawbacks, digitalcontact tracing has been proposed that typically involves deploying a contacttracing application on people's mobile devices which can track their movementsand close social interactions. While studies suggest that digital contacttracing is more effective than manual contact tracing, it has been observedthat higher adoption rates of the contact tracing app may result in a bettercontrolled epidemic. This also increases the confidence in the accuracy of thecollected data and the subsequent analytics. One key reason for low adoptionrate of contact tracing applications is the concern about individual privacy.In fact, several studies report that contact tracing applications deployed inmultiple countries are not privacy friendly and have potential to be used formass surveillance by the concerned governments. Hence, privacy respectingcontact tracing application is the need of the hour that can lead to highlyeffective, efficient contact tracing. As part of this study, we focus onvarious cryptographic techniques that can help in addressing the Private SetIntersection problem which lies at the heart of privacy respecting contacttracing. We analyze the computation and communication complexities of thesetechniques under the typical client-server architecture utilized by contacttracing applications. Further we evaluate those computation and communicationcomplexity expressions for India scenario and thus identify cryptographictechniques that can be more suitably deployed there.

A Note on Cryptographic Algorithms for Private Data Analysis in Contact Tracing Applications