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