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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Xinyi Xie (Shanghai Fudan Microelectronics Group Co., Ltd.), Kun Jiang (Shanghai Fudan Microelectronics Group Co., Ltd.), Rui Dai (Shanghai Fudan Microelectronics Group Co., Ltd.), Jun Lu (Shanghai Fudan Microelectronics Group Co., Ltd.), Lihui Wang (Shanghai Fudan Microelectronics Group Co., Ltd.), Qing Li (State Key Laboratory of ASIC & System, Fudan University), Jun Yu (State Key…

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Dr. Zhiqiang Lin (Distinguished Professor of Engineering at The Ohio State University)

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Eric Pauley and Patrick McDaniel (University of Wisconsin–Madison)

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

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