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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Security Advice on Content Filtering and Circumvention for Parents...

Ran Elgedawy (The University of Tennessee, Knoxville), John Sadik (The University of Tennessee, Knoxville), Anuj Gautam (The University of Tennessee, Knoxville), Trinity Bissahoyo (The University of Tennessee, Knoxville), Christopher Childress (The University of Tennessee, Knoxville), Jacob Leonard (The University of Tennessee, Knoxville), Clay Shubert (The University of Tennessee, Knoxville), Scott Ruoti (The University of Tennessee,…

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Tactics, Threats & Targets: Modeling Disinformation and its Mitigation

Shujaat Mirza (New York University), Labeeba Begum (New York University Abu Dhabi), Liang Niu (New York University), Sarah Pardo (New York University Abu Dhabi), Azza Abouzied (New York University Abu Dhabi), Paolo Papotti (EURECOM), Christina Pöpper (New York University Abu Dhabi)

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Accurate Compiler and Optimization Independent Function Identification Using Program...

Derrick McKee (Purdue University), Nathan Burow (MIT Lincoln Laboratory), Mathias Payer (EPFL)

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