  Crowdsourcing technologies rely on groups of people to input information that
may be critical for decision-making. This work examines obfuscation in the
context of reporting technologies. We show that widespread use of reporting
platforms comes with unique security and privacy implications, and introduce a
threat model and corresponding taxonomy to outline some of the many attack
vectors in this space. We then perform an empirical analysis of a dataset of
call logs from a controversial, real-world reporting hotline and identify
coordinated obfuscation strategies that are intended to hinder the platform's
legitimacy. We propose a variety of statistical measures to quantify the
strength of this obfuscation strategy with respect to the structural and
semantic characteristics of the reporting attacks in our dataset.
