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Inverse document frequency-based sensitivity scoring for privacy analysis

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Abstract

Privacy risk analysis of online social network (OSN) users aims at generating a risk score for each OSN user such that higher scores potentially imply a greater risk of privacy violation. Privacy risk analysis is typically carried out over a response matrix (R) where any matrix element \(r_{ij}\) indicates the portion of the OSN that the user i shares his/her attribute j. Most of the existing work relies on the mathematical framework of item response theory to derive sensitivity and visibility components from R. In this study, we propose interpreting R to be a term–document matrix and consequently suggest using the inverse document frequency (IDF) method as the sensitivity component. Experiments performed on both synthetic and real-world datasets show that the proposed IDF-based method can be used as a sensitivity component.

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Notes

  1. https://crypto.stanford.edu/socialnetsec/media/kunliu_privacy_score_stanford_0911.pdf.

  2. https://cran.r-project.org/web/packages/ltm/ltm.pdf.

  3. Not all of user risk scores are given to save space.

  4. The scores given in Table 3 are calculated only on 5 \(\times \) 16-dimensional dichotomous R matrix given in Table 2. However, the total risk scores given in Table 2 were calculated over the entire synthetic response data with a size of 5 K \(\times \) 16.

  5. https://docs.scipy.org/doc/scipy/reference/stats.html.

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Authors and Affiliations

  1. Department of Computer Engineering, Cukurova University, Adana, Turkey

    Onder Coban

  2. Department of Computer Engineering, Adana Alparslan Turkes Science and Technology University, Adana, Turkey

    Ali Inan

  3. Department of Computer Engineering, Cukurova University, Adana, Turkey

    Selma Ayse Ozel

Authors
  1. Onder Coban
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  2. Ali Inan
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  3. Selma Ayse Ozel
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Correspondence to Onder Coban.

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Coban, O., Inan, A. & Ozel, S.A. Inverse document frequency-based sensitivity scoring for privacy analysis. SIViP 16, 735–743 (2022). https://doi.org/10.1007/s11760-021-02013-1

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  • DOI: https://doi.org/10.1007/s11760-021-02013-1

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