On the privacy of horizontally partitioned binary data-based privacy-preserving collaborative filtering

Okkalioglu M., KOÇ M., Polat H.

10th International Workshop on Data Privacy Management, and Security Assurance, DPM 2015 and 4th International Workshop on Quantitative Aspects in Security Assurance, QASA 2015, Vienna, Avusturya, 21 - 22 Eylül 2015, cilt.9481, ss.199-214, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 9481
  • Doi Numarası: 10.1007/978-3-319-29883-2_13
  • Basıldığı Şehir: Vienna
  • Basıldığı Ülke: Avusturya
  • Sayfa Sayıları: ss.199-214
  • Anahtar Kelimeler: Attack scenarios, Binary data, Collaborative filtering, Privacy
  • Bilecik Şeyh Edebali Üniversitesi Adresli: Evet

Özet

© Springer International Publishing Switzerland 2016.Collaborative filtering systems provide recommendations for their users. Privacy is not a primary concern in these systems; however, it is an important element for the true user participation. Privacy-preserving collaborative filtering techniques aim to offer privacy measures without neglecting the recommendation accuracy. In general, these systems rely on the data residing on a central server. Studies show that privacy is not protected as much as believed. On the other hand, many e-companies emerge with the advent of the Internet, and these companies might collaborate to offer better recommendations by sharing their data. Thus, partitioned data-based privacy-persevering collaborative filtering schemes have been proposed. In this study, we explore possible attacks on two-party binary privacy-preserving collaborative filtering schemes and evaluate them with respect to privacy performance.