STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Communications of the ACM
Multiparty Computation from Threshold Homomorphic Encryption
EUROCRYPT '01 Proceedings of the International Conference on the Theory and Application of Cryptographic Techniques: Advances in Cryptology
An Unconditionally Secure Protocol for Multi-Party Set Intersection
ACNS '07 Proceedings of the 5th international conference on Applied Cryptography and Network Security
TCC '09 Proceedings of the 6th Theory of Cryptography Conference on Theory of Cryptography
Private Intersection of Certified Sets
Financial Cryptography and Data Security
CANS '09 Proceedings of the 8th International Conference on Cryptology and Network Security
Round Efficient Unconditionally Secure MPC and Multiparty Set Intersection with Optimal Resilience
INDOCRYPT '09 Proceedings of the 10th International Conference on Cryptology in India: Progress in Cryptology
Privacy-preserving set operations
CRYPTO'05 Proceedings of the 25th annual international conference on Advances in Cryptology
Practical private set intersection protocols with linear complexity
FC'10 Proceedings of the 14th international conference on Financial Cryptography and Data Security
Honest-verifier private disjointness testing without random oracles
PET'06 Proceedings of the 6th international conference on Privacy Enhancing Technologies
Design and implementation of privacy-preserving reconciliation protocols
Proceedings of the Joint EDBT/ICDT 2013 Workshops
Hi-index | 0.00 |
In this paper, we introduce the first protocols for multiparty, privacy-preserving, fair reconciliation of ordered sets. Our contributions are twofold. First, we show that it is possible to extend the round-based construction for fair, two-party privacy-preserving reconciliation of ordered sets to multiple parties using a multiparty privacy-preserving set intersection protocol. Second, we propose new constructions for fair, multi-party, privacy-preserving reconciliation of ordered sets based on multiset operations. We prove that all our protocols are privacy-preserving in the semi-honest model.We furthermore provide a detailed performance analysis of our new protocols and show that the constructions based on multisets generally outperform the round-based approach.