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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Cloud-Hosted Security Operations Center (SOC)

Drew Walsh, Kevin Conklin (Deloitte)

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Towards Automatic and Precise Heap Layout Manipulation for General-Purpose...

Runhao Li (National University of Defense Technology), Bin Zhang (National University of Defense Technology), Jiongyi Chen (National University of Defense Technology), Wenfeng Lin (National University of Defense Technology), Chao Feng (National University of Defense Technology), Chaojing Tang (National University of Defense Technology)

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A Field Study to Uncover and a Tool to...

Leon Kersten (Eindhoven University of Technology), Kim Beelen (Eindhoven University of Technology), Emmanuele Zambon (Eindhoven University of Technology), Chris Snijders (Eindhoven University of Technology), Luca Allodi (Eindhoven University of Technology)

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A Systematic Study of the Consistency of Two-Factor Authentication...

Sanam Ghorbani Lyastani (CISPA Helmholtz Center for Information Security, Saarland University), Michael Backes (CISPA Helmholtz Center for Information Security), Sven Bugiel (CISPA Helmholtz Center for Information Security)

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