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.

View More Papers

Copy-on-Flip: Hardening ECC Memory Against Rowhammer Attacks

Andrea Di Dio (Vrije Universiteit Amsterdam), Koen Koning (Intel), Herbert Bos (Vrije Universiteit Amsterdam), Cristiano Giuffrida (Vrije Universiteit Amsterdam)

Read More

Understanding the Ethical Frameworks of Internet Measurement Studies

Eric Pauley and Patrick McDaniel (University of Wisconsin–Madison)

Read More

BlockScope: Detecting and Investigating Propagated Vulnerabilities in Forked Blockchain...

Xiao Yi (The Chinese University of Hong Kong), Yuzhou Fang (The Chinese University of Hong Kong), Daoyuan Wu (The Chinese University of Hong Kong), Lingxiao Jiang (Singapore Management University)

Read More

FCGAT: Interpretable Malware Classification Method using Function Call Graph...

Minami Someya (Institute of Information Security), Yuhei Otsubo (National Police Academy), Akira Otsuka (Institute of Information Security)

Read More