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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Anomaly Detection in the Open World: Normality Shift Detection,...

Dongqi Han (Tsinghua University), Zhiliang Wang (Tsinghua University), Wenqi Chen (Tsinghua University), Kai Wang (Tsinghua University), Rui Yu (Tsinghua University), Su Wang (Tsinghua University), Han Zhang (Tsinghua University), Zhihua Wang (State Grid Shanghai Municipal Electric Power Company), Minghui Jin (State Grid Shanghai Municipal Electric Power Company), Jiahai Yang (Tsinghua University), Xingang Shi (Tsinghua University), Xia…

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Understanding MPU Usage in Microcontroller-based Systems in the Wild

Wei Zhou, Zhouqi Jiang (School of Cyber Science and Engineering, Huazhong University of Science and Technology), Le Guan (School of Computing, University of Georgia)

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More than Meets the Eye: Understanding the Effect of...

Mete Harun Akcay (Abo Academy University), Siddarth Prakash Rao (Nokia Bell Labs), Alexandros Bakas (Nokia Bell Labs), Buse Atli (Linkoping University)

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