TY - GEN
T1 - Using secure graph algorithms for the privacy-preserving identification of optimal bartering opportunities
AU - Wüller, Stefan
AU - Vu, Michael
AU - Meyer, Ulrike
AU - Wetzel, Susanne
N1 - Publisher Copyright:
© 2017 Association for Computing Machinery.
PY - 2017/10/30
Y1 - 2017/10/30
N2 - We present a novel bartering protocol that allows multiple parties to identify their trade partners in a privacy-preserving fashion while maximizing the number of parties that can trade. Compared to existing approaches, the (polynomial) time complexity of our protocol is independent of the size of the search space which grows exponentially in the number of parties. At the core of our protocol is a novel privacy-preserving implementation of the Hungarian algorithm which allows multiple parties to compute a weighted maximum matching on a private input graph.
AB - We present a novel bartering protocol that allows multiple parties to identify their trade partners in a privacy-preserving fashion while maximizing the number of parties that can trade. Compared to existing approaches, the (polynomial) time complexity of our protocol is independent of the size of the search space which grows exponentially in the number of parties. At the core of our protocol is a novel privacy-preserving implementation of the Hungarian algorithm which allows multiple parties to compute a weighted maximum matching on a private input graph.
KW - Bartering
KW - E-Commerce
KW - Homomorphic encryption
KW - Privacy
KW - Secure multi-party computation
UR - http://www.scopus.com/inward/record.url?scp=85043394746&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85043394746&partnerID=8YFLogxK
U2 - 10.1145/3139550.3139557
DO - 10.1145/3139550.3139557
M3 - Conference contribution
AN - SCOPUS:85043394746
T3 - WPES 2017 - Proceedings of the 2017 Workshop on Privacy in the Electronic Society, co-located with CCS 2017
SP - 123
EP - 132
BT - WPES 2017 - Proceedings of the 2017 Workshop on Privacy in the Electronic Society, co-located with CCS 2017
T2 - 16th ACM Workshop on Privacy in the Electronic Society, WPES 2017
Y2 - 30 October 2017
ER -