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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Dongyao Chen (Shanghai Jiao Tong University), Mert D. Pesé (Clemson University), Kang G. Shin (University of Michigan, Ann Arbor)

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Tianyang Chen (Huazhong University of Science and Technology), Peng Xu (Huazhong University of Science and Technology), Stjepan Picek (Radboud University), Bo Luo (The University of Kansas), Willy Susilo (University of Wollongong), Hai Jin (Huazhong University of Science and Technology), Kaitai Liang (TU Delft)

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Muhammad Irtaza Safi, Abhiditya Jha (University of Central Florida); Malak Eihab Aly (New York University); Xinru Page (Bentley University); Sameer Patil (Indiana University); Pamela Wisniewski (University of Central Florida)

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Tommaso Frassetto (Technical University of Darmstadt), Patrick Jauernig (Technical University of Darmstadt), David Koisser (Technical University of Darmstadt), David Kretzler (Technical University of Darmstadt), Benjamin Schlosser (Technical University of Darmstadt), Sebastian Faust (Technical University of Darmstadt), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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