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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Dev Vikesh Doshi (California State University San Marcos), Mehjabeen Tasnim (California State University San Marcos), Fernando Landeros (California State University San Marcos), Chinthagumpala Muni Venkatesh (California State University San Marcos), Daniel Timko (Emerging Threats Lab / Smishtank.com), Muhammad Lutfor Rahman (California State University San Marcos)

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Exploiting Transport Protocol Vulnerabilities in SAE J1939 Networks

Rik Chatterjee, Subhojeet Mukherjee, Jeremy Daily (Colorado State University)

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An OS-agnostic Approach to Memory Forensics

Andrea Oliveri (EURECOM), Matteo Dell'Amico (University of Genoa), Davide Balzarotti (EURECOM)

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