In Lieu of Privacy: Anonymous Contact Tracing
This work addresses the need for fast and anonymous disease tracking for public health, though it appears incremental as it builds on an existing protocol.
The paper tackles the problem of privacy-preserving contact tracing for diseases spread by proximity, such as seasonal flu and COVID-19, by introducing Tracer Tokens, a hardware token that uses the Exposure Notification protocol to notify n^n users in parallel, achieving unmatched speed compared to current methods.
We present Tracer Tokens, a hardware token of privacy-preserving contact tracing utilizing Exposure Notification \cite{GAEN} protocol. Through subnetworks, we show that any disease spread by proximity can be traced such as seasonal flu, cold, regional strains of COVID-19, or Tuberculosis. Further, we show this protocol to notify $n^n$ users in parallel, providing a speed of information unmatched by current contact tracing methods.