Inverse document frequency-based sensitivity scoring for privacy analysis
[ X ]
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer London Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
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.
Açıklama
Anahtar Kelimeler
Privacy risk analysis, Online social networks, Inverse-document frequency
Kaynak
Signal Image and Video Processing
WoS Q Değeri
Q4
Scopus Q Değeri
Q2
Cilt
16
Sayı
3
