Privately Computing Set-Union and Set-Intersection Cardinality via Bloom Filters

@inproceedings{Egert2015PrivatelyCS,
  title={Privately Computing Set-Union and Set-Intersection Cardinality via Bloom Filters},
  author={Rolf Egert and Marc Fischlin and David Gens and Sven Jacob and Matthias Senker and J{\"o}rn Tillmanns},
  booktitle={ACISP},
  year={2015}
}
In this paper we propose a new approach to privately compute the set-union cardinality and the set-intersection cardinality among multiple honest-but-curious parties. Our approach is inspired by a proposal of Ashok and Mukkamala (DBSec’14) which deploys Bloom filters to approximate the size tightly. One advantage of their solution is that it avoids ample public-key cryptography. Unfortunately, we show here that their protocol is vulnerable to actual attacks. We therefore propose a new Bloom… CONTINUE READING
Highly Cited
This paper has 178 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 17 extracted citations

Approximating Private Set Union/Intersection Cardinality With Logarithmic Complexity

IEEE Transactions on Information Forensics and Security • 2017
View 10 Excerpts
Highly Influenced

Computing Private Set Operations with Linear Complexities

IACR Cryptology ePrint Archive • 2016
View 5 Excerpts
Highly Influenced

Privacy-Preserving Integration of Medical Data

Journal of Medical Systems • 2016
View 5 Excerpts
Highly Influenced

Do You Like What I Like? Similarity Estimation in Proximity-Based Mobile Social Networks

2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE) • 2018
View 1 Excerpt

Efficient and Quasi-accurate Multiparty Private Set Union

2018 IEEE International Conference on Smart Computing (SMARTCOMP) • 2018
View 1 Excerpt

178 Citations

0501001502016201720182019
Citations per Year
Semantic Scholar estimates that this publication has 178 citations based on the available data.

See our FAQ for additional information.

Similar Papers

Loading similar papers…