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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Takami Sato (University of California, Irvine), Sri Hrushikesh Varma Bhupathiraju (University of Florida), Michael Clifford (Toyota InfoTech Labs), Takeshi Sugawara (The University of Electro-Communications), Qi Alfred Chen (University of California, Irvine), Sara Rampazzi (University of Florida)

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Cloud-Hosted Security Operations Center (SOC)

Drew Walsh, Kevin Conklin (Deloitte)

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Sometimes, You Aren’t What You Do: Mimicry Attacks against...

Akul Goyal (University of Illinois at Urbana-Champaign), Xueyuan Han (Wake Forest University), Gang Wang (University of Illinois at Urbana-Champaign), Adam Bates (University of Illinois at Urbana-Champaign)

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Vision: Towards True User-Centric Design for Digital Identity Wallets

Yorick Last (Paderborn University), Patricia Arias Cabarcos (Paderborn University)

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