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Verifiable Threshold Secret Sharing and Full Fair Secure Two-party Computation YE Jian-wei March 7, 2009
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outline Full fair secure two-party computation – Problem – Existing methods Our method – Overview – Advantages – Cryptography foundation – New Full Fair Secure Two-party Computation Protocol
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Full fair secure two-party computation ——problem two parties A with input x and B with input y jointly compute a two output function f(x,y)=(f A (x,y), f B (x,y)) Secure: A learn only x and f A (x,y) B learn only y and f B (x,y) Fair: A learns f A (x,y) iff B learns f B (x,y)
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For security – Garbled circuit computation For fairness – gradual release technique – Methods employing trusted third party Full fair secure two-party computation ——existing methods
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gradual release technique Without third parties at the cost of many rounds of interaction impossible to get full fairness Full fair secure two-party computation ——existing methods
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Methods employing trusted third party full fairness the trusted third party must be neutral (doesn’t collude with A or B) single point of failure the performance bottleneck Full fair secure two-party computation ——existing methods
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Our method——overview full fairness employ Yao’s garbled circuit computation for security employ a group of servers as the third party for full fairness
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Our method——advantages 1. Weakening the trust assumption. Our method doesn’t require all third-party servers are trusted, but just require more than two-third of them are honest. 2. Protection against collusion. Our method can keep the fairness when less than one-third of the servers are dishonest (or malicious) and collude with the any party.
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Our method——advantages 3. Fault-tolerance. In our method, not all servers must be always available. More precisely, when the count of the dishonest servers is m, only 3m+1 servers are needed simultaneously.
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Our method——Cryptography foundation 1. Garbled circuit computation 2. Verifiable encryption scheme of Jarecki and Shmatikov (sCS encryption scheme) 3. zero-knowledge proof (ZKP) protocols of Jarecki and Shmatikov 4. Verifiable threshold secret sharing (VTSS) scheme of Pedersen
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Garbled circuit computation 1. A constructs a boolean circuit, C, computing f(x,y) 2. A garbles C to GC 3. A sends GC, the garbled x and the cleartext interpretation of f B (x,y) to B 4. B gets the garbled y form A 5. B computes GC and gets its output, garbled f A (x,y) and garbled f B (x,y) 6. B ungarbles the garbled f B (x,y) to get f B (x,y) by the cleartext interpretation of f B (x,y) 7. B sends the garbled f A (x,y) to A 8. A ungarbles the garbled f A (x,y) to get f A (x,y)
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sCS encryption scheme a simplification of the verifiable encryption scheme of Camenisch and Shoup semantically secure in CRS model under DCR assumption and safe RSA moduli. a very strong unambiguous encryption. a ciphertext that passes a certain proof system cannot decrypt to two different plaintexts under two different private keys. Moreover, no two distinct decryption keys can decrypt a ciphertext even to the same plaintext.
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sCS encryption scheme CRS.
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sCS encryption scheme sCS encryption.
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sCS encryption scheme sCS decryption.
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ZKP protocols of Jarecki and Shmatikov Relying on the Unambiguity of sCS encryption scheme, Jarecki and Shmatikov proposed the sCS commitment scheme and a group of efficient concurrently secure ZKP protocols. sCS commitment scheme
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ZKP protocols of Jarecki and Shmatikov ZKP protoclos – ZKDL( ɡ, X) is used to prove that there exists a x s.t. X 2 = ɡ 2x. – ZKNotEq(C a, C b ) is used to prove that C a, C b are sCS commitments to different values. – ZKPlainEq((u, e),C k, C m ) is used to prove that (u, e) is a sCS encryption of cleartext m committed (sCS commitment) in C m under the key k committed in C k.
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VTSS scheme of Pedersen Pedersen gave a semantically secure commitment scheme based on the difficulty of discrete logarithm problem, and proposed a VTSS scheme in the CRS model by it. CRS
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VTSS scheme of Pedersen Pedersen’s commitment scheme
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VTSS scheme of Pedersen Sharing and Verifying process
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New Full Fair Secure Two-party Computation Protocol New ZKP protocol ZKEq( C K D,C K D ) prove that the sCS commitment C K D commits the same value as the Pedersen’s commitment C K D
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New Full Fair Secure Two-party Computation Protocol——overview In usual garbled circuit computation A send the cleartext interpretation of f B (x,y) to B, therefore the circuit evaluator B may not send garbled f A (x,y) to A after get his output f B (x,y). In our protocol A commits all output wire keys corresponding f B (x,y) in GC A shares a private key K D ∈ [0,2 k′′ ] among a group of third- party servers by VTSS scheme of Pedersen A provides B an encrypted cleartext interpretation of f B (x,y), CI B
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New Full Fair Secure Two-party Computation Protocol——overview By correctly performing all ZKP protocols involved in following formula with A and verifying process of Pedersen’s VTSS scheme, B is convinced that CI B is correctly constructed and able to be decrypted with the key (i.e. K D ) shared in the servers, and he can retrieve the key to decrypt CI B as long as sending correct output keys corresponding to f A (x,y) to the servers.
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New Full Fair Secure Two-party Computation Protocol——overview
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After sending correct output wire keys corresponding to f A (x,y) to the servers, B gets enough shares of K D to retrieve it and compute his output f B (x,y). Henceforth, A can compute his output f A (x,y) even if B sends him wrong output wire keys by obtaining correct these from the servers.
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New Full Fair Secure Two-party Computation Protocol——protocol
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New Full Fair Secure Two-party Computation Protocol——analyse Fairness When the amount of dishonest servers m is less than s/3 , our protocol is able to guarantee that A learns f A (x,y) iff B learns f B (x,y). Complexity Computational complexity is O(S+s 2 ) Communication complexity is O(S+s) only two additional interaction rounds for full fair where S is the size of the circuit and s is the amount of employed servers.
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END! THANKS!
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