Applied Cryptography and Network Security: 13th by Tal Malkin, Vladimir Kolesnikov, Allison Lewko, Michalis
By Tal Malkin, Vladimir Kolesnikov, Allison Lewko, Michalis Polychronakis
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Additional info for Applied Cryptography and Network Security: 13th International Conference, ACNS 2015, New York, NY, USA, June 2-5, 2015, Revised Selected Papers
Xm ), C, a) is the random variable, given security parameter k, consisting of all parties’ outputs and O. Definition 3. Protocol π implements veriﬁable secure function evaluation in the random oracle model if, for every probabilistic polynomial time real-world adversary A, there exists a probabilistic polynomial time ideal-world adversary SA such that, for all inputs x1 , . . , xm ; all sets of corrupted parties C; and all auxiliary input a: EXECπ,A (k; x1 , . . , xm ; C; a) and IDEALTVSFE ,SA (k; x1 , .
Communication-Optimal Proactive Secret Sharing for Dynamic Groups 29 In , this issue is prevented by constructing the polynomial Q such that no party in the old group knows her share of Q. More speciﬁcally, the parties in the old group construct a polynomial Rj for each Pj in the new group such that Rj (βj ) = 0. Then the Q and the Rj are generated simultaneously so that each party in the old group only learns her share of Q + Rj for each j. This technique preserves security but would not yield the optimal communication bandwidth that we aim for.
Security deﬁnitions and proofs are given in the full version of this paper . 2 Related Work The same work  introducing the proactive security model also contained the ﬁrst proactive secret sharing (PSS) scheme and proactively-secure multiparty computation (PMPC) protocol. PSS was the central tool introduced in , and there has been signiﬁcant follow up work on PSS schemes, both in the synchronous and asynchronous network models (see Table 1 for a comparison). Currently the most eﬃcient (non-dynamic) PSS scheme is , which has an optimal O(1) amortized communication complexity per secret share, is UC-secure and achieves near-optimal thresholds for both perfect and statistical cases.