  The COVID-19 pandemic has caused many countries to deploy novel digital
contact tracing (DCT) systems to boost the efficiency of manual tracing of
infection chains. In this paper, we systematically analyze DCT solutions and
categorize them based on their design approaches and architectures. We analyze
them with regard to effectiveness, security, privacy, and ethical aspects and
compare prominent solutions with regard to these requirements. In particular,
we discuss the shortcomings of the Google and Apple Exposure Notification API
(GAEN) that is currently widely adopted all over the world. We find that the
security and privacy of GAEN have considerable deficiencies as it can be
compromised by severe, large-scale attacks. We also discuss other proposed
approaches for contact tracing, including our proposal TRACECORONA, that are
based on Diffie-Hellman (DH) key exchange and aim at tackling shortcomings of
existing solutions. Our extensive analysis shows thatTRACECORONA fulfills the
above security requirements better than deployed state-of-the-art approaches.
We have implementedTRACECORONA, and its beta test version has been used by more
than 2000 users without any major functional problems, demonstrating that there
are no technical reasons requiring to make compromises with regard to the
requirements of DCTapproaches.
