TY - GEN
T1 - Fair and efficient secure multiparty computation with reputation systems
AU - Asharov, Gilad
AU - Lindell, Yehuda
AU - Zarosim, Hila
N1 - Funding Information: This research was supported by the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 239868.
PY - 2013
Y1 - 2013
N2 - A reputation system for a set of entities is essentially a list of scores that provides a measure of the reliability of each entity in the set. The score given to an entity can be interpreted (and in the reputation system literature it often is [12]) as the probability that an entity will behave honestly. In this paper, we ask whether or not it is possible to utilize reputation systems for carrying out secure multiparty computation. We provide formal definitions of secure computation in this setting, and carry out a theoretical study of feasibility. We present almost tight results showing when it is and is not possible to achieve fair secure computation in our model. We suggest applications for our model in settings where some information about the honesty of other parties is given. This can be preferable to the current situation where either an honest majority is arbitrarily assumed, or a protocol that is secure for a dishonest majority is used and the efficiency and security guarantees (including fairness) of an honest majority are not obtained.
AB - A reputation system for a set of entities is essentially a list of scores that provides a measure of the reliability of each entity in the set. The score given to an entity can be interpreted (and in the reputation system literature it often is [12]) as the probability that an entity will behave honestly. In this paper, we ask whether or not it is possible to utilize reputation systems for carrying out secure multiparty computation. We provide formal definitions of secure computation in this setting, and carry out a theoretical study of feasibility. We present almost tight results showing when it is and is not possible to achieve fair secure computation in our model. We suggest applications for our model in settings where some information about the honesty of other parties is given. This can be preferable to the current situation where either an honest majority is arbitrarily assumed, or a protocol that is secure for a dishonest majority is used and the efficiency and security guarantees (including fairness) of an honest majority are not obtained.
KW - new models
KW - reputation systems
KW - secure multiparty computation
UR - https://www.scopus.com/pages/publications/84892377298
U2 - 10.1007/978-3-642-42045-0_11
DO - 10.1007/978-3-642-42045-0_11
M3 - Conference contribution
SN - 9783642420443
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 201
EP - 220
BT - Advances in Cryptology, ASIACRYPT 2013 - 19th International Conference on the Theory and Application of Cryptology and Information Security, Proceedings
T2 - 19th International Conference on the Theory and Application of Cryptology and Information Security, ASIACRYPT 2013
Y2 - 1 December 2013 through 5 December 2013
ER -