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Stop the Open Data Bus, We Want to Get Off

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arxiv 1908.05004 v1 pith:SKOUCT34 submitted 2019-08-14 cs.CR

classification cs.CR
keywords datareleasedabilityableanalysisco-travellerscompleteconcerns
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The subject of this report is the re-identification of individuals in the Myki public transport dataset released as part of the Melbourne Datathon 2018. We demonstrate the ease with which we were able to re-identify ourselves, our co-travellers, and complete strangers; our analysis raises concerns about the nature and granularity of the data released, in particular the ability to identify vulnerable or sensitive groups.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Breaking the $n^{1.5}$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition

    cs.DS 2025-07 conditional novelty 7.0 of 10

    A polynomial-time differentially private algorithm approximates every cut in a graph within (1+γ) multiplicative and n^{1.25+o(1)} additive error, breaking the previous n^{1.5} barrier.

  2. Investigating Vulnerabilities of GPS Trip Data to Trajectory-User Linking Attacks

    cs.CR 2025-02 conditional novelty 6.0 of 10

    A heuristic attack reconstructs user identifiers in GPS trip data by exploiting trip continuation, home locations, and TF-IDF location co-visits, showing significant re-identification risk and unreliable protection fr...

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