Kaustav Bhattacharjee, Aritra Dasgupta (New Jersey Institute of Technology)

The open data ecosystem is susceptible to vulnerabilities due to disclosure risks. Though the datasets are anonymized during release, the prevalence of the release-and-forget model makes the data defenders blind to privacy issues arising after the dataset release. One such issue can be the disclosure risks in the presence of newly released datasets which may compromise the privacy of the data subjects of the anonymous open datasets. In this paper, we first examine some of these pitfalls through the examples we observed during a red teaming exercise and then envision other possible vulnerabilities in this context. We also discuss proactive risk monitoring, including developing a collection of highly susceptible open datasets and a visual analytic workflow that empowers data defenders towards undertaking dynamic risk calibration strategies.

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Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

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U.S. Election Expert Perspectives on End-to-end Verifiable Voting Systems

Julie M. Haney (National Institute of Standards and Technology, Gaithersburg, Maryland), Shanee Dawkins (National Institute of Standards and Technology, Gaithersburg, Maryland), Sandra Spickard Prettyman (Cultural Catalyst LLC, Chicago), Mary F. Theofanos (National Institute of Standards and Technology, Gaithersburg, Maryland), Kristen K. Greene (National Institute of Standards and Technology, Gaithersburg, Maryland), Kristin L. Kelly Koskey (Cultural Catalyst LLC, Chicago), Jody L. Jacobs (National Institute of Standards…

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Cybercrime Investigators are Users Too! Understanding the Socio-Technical Challenges...

Mariam Nouh (University of Oxford); Jason R. C. Nurse (University of Kent); Helena Webb, Michael Goldsmith (University of Oxford)

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