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Title: Collective Obfuscation and Crowdsourcing
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.  more » « less
Award ID(s):
1704527
PAR ID:
10437762
Author(s) / Creator(s):
;
Date Published:
Journal Name:
KDD MIS2-TrueFact and ICML DisCoML Workshops
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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