on diophantine complexity and statistical zero knowledge
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On Diophantine Complexity and Statistical Zero-Knowledge Arguments Helger Lipmaa Helsinki University of Technology http://www.tcs.hut.fi/helger Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 1


  1. On Diophantine Complexity and Statistical Zero-Knowledge Arguments Helger Lipmaa Helsinki University of Technology http://www.tcs.hut.fi/˜helger Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 1

  2. Overview of This Talk • Cryptographic protocols, limitations • Outsourcing model • Polynomials and integer commitment schemes • Efficient solutions by using diophantine complexity Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 2

  3. Reminder: Multi-Party Computation • All efficiently computable functions can also be computed securely • Assume there are n participants, and the i th participant has input x i . Assume f is a function f ( x 1 , . . . , x n ) = ( y 1 , . . . , y n ) . • There is a way ( multi-party computation ) to compute f so that at the end of the protocol, the i th participant will get the know value of y i and nothing else, except what she could compute from ( x i , y i ) herself. Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 3

  4. We Gotta Have Some Pictures Karl I Karl II Karl III f Karl n − 1 Karl n Assume f is any function. Karl’s can compute f so that (a) Security: Karl i obtains the output he wanted to obtain, (b) Privacy: Karl i will not obtain any new information that cannot be computed from his input and output alone. Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 4

  5. Applications: Voting • n voters, one tallier. • Voter i has input v i , her vote. • Security: Tallier gets to know y T := � n i =1 v i . • Privacy: Tallier will not get any information that cannot be computed from y T alone. Voters will not get any new information at all. Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 5

  6. Limitations • MPC: To get total privacy and security, a majority of the parties must be honest (in some settings, 2 / 3 !) • “Threshold trust” in voting: assume that a majority of talliers and/or voters is honest? • Two-party computation: privacy possible, but security is possible only for one of the two parties (since he can halt as soon as he recovers his output) • Fortunately, often one can design protocols, where halting is not a problem — but not always Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 6

  7. Outsourcing model • n individuals, 1 interested third party S , one established authority A . • Individual i has input v i , her financial or social choice (vote, bid, . . . ). • Security: S gets to know y T := f ( v 1 , . . . , v n ) for some destination function f . • Privacy: S will not get any information that cannot be computed from y T alone. Individuals will not get any new information at all. A can get to know the vector ( v 1 , . . . , v n ) . Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 7

  8. Why makes sense? • In voting, it is better to have one tallier: in real life, very hard to have a multiple of completely independent talliers. • Same in auctions: there is a single seller, all servers are operated by him; why should we trust m machines controlled by the same person more than just one machine, controlled by him? • OTOH: A can be an established authority who has a reputation to take care off; often S is an occassional party. • It is also possible to design the system so that we can avoid the limita- tions of the two-party and multi-party computations, efficiently Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 8

  9. Example: Vickrey Auctions Security requirements: • Correctness ⋆ Highest bidder Y 1 should win ⋆ He should pay the second highest bid X 2 • Privacy: S should not get any information about the bids but ( Y 1 , X 2 ) • Scheme should be secure unless both A and S are malicious Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 9

  10. ☎ ✆ ✄ ✄ � ☎ ☎ ✆ ✝ ✄ ✝ ✝ ✝ ✝ ✝ ✝ ✝ ✄ ✂ ✝ � � � � � � � � ✁ ✂ ✁ ✁ ✁ ✁ ✁ ✂ ✂ ✝ Simple scheme 1 Bid b i encrypted with A -s key 2 Send bids in shuffled order 3 Decrypt bids, send Y 1 , X 2 to S 4 Send acknowledgment S will not get any extra information, but S can increase X 2 A → S interaction is quite large Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 10

  11. ✄ ✆ ✄ ✝ ✄ ☎ ☎ ☎ ✆ ✂ ✝ ✝ ✝ ✝ ✝ ✝ ✝ ✄ ✂ ✝ � � � � � � � � � ✂ ✁ ✁ ✁ ✁ ✁ ✁ ✂ ✝ Simple scheme → complex scheme 1 Bid b i encrypted with A -s key 2 Send bids in shuffled order 3 Decrypt bids, send Y 1 , X 2 to S 4 Send acknowledgment Add correctness proofs Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 11

  12. Proofs of correctness 1. Complex: use bulletin board, argue that bid belongs to some set 2. Complex: combine bids, argue correctness of combination 3. Complex: extract X 2 , argue it 4. Simple: ( Y 1 , X 2 ) signed by S Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 12

  13. Efficient Proofs of Knowledge 1. Bidders encode their bids by using some function enc ( · ) , and then en- crypt the result by using A ’s key. They send the result, E K ( enc ( b i ); r i ) to S 2. S multiplies the results, gets E K ( � enc ( b i ); � r i ) ; sends the result to A 3. A decrypts the result, obtains � enc ( b i ) , applies a decoding function to it and obtains ( b 1 , . . . , b n ) 4. A computes o = f ( b 1 , . . . , b n ) , sends this to S and argues that o was correctly computed Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 13

  14. Details! 1. E is homomorphic: E K ( m 1 ; r 1 ) E ( m 2 ; r 2 ) = E K ( m 1 + m 2 ; r 1 + r 2 ) — such E are well-known (Paillier, . . . ) 2. There exists enc ( · ) and dec ( · ) , such that dec ( � enc ( b i )) = ( b 1 , . . . , b n ) for all b 1 from [0 , V − 1] — for example, take enc ( b i ) = V b i ; then dec ( b ) returns the vector of V -radix positions of b 3. Thus a bidder must argue that c i is an encryption of V b i for b i ∈ [0 , V − 1] , and A must argue that o = f ( dec ( � enc ( b i )) Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 14

  15. Problems! 1. Known arguments that c i = E K ( V µ ; ρ ) ∧ µ ∈ [0 , V − 1] are long [DJ01,LAN02] 2. Efficient arguments for o = f ( dec ( � enc ( b i )) are known only for a very limited set of f -s 3. For example, in Vickrey auctions one needs to argue that c = E K ( µ ; ρ ) ∧ µ ∈ [0 , V − 1] ; even for this range argument, con- ventional arguments are too long. Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 15

  16. Integer commitment schemes • Commitment scheme: c = C K ( µ ; ρ ) . c does not give Hiding: Binding: hard to find µ ′ � = µ such that any information about µ . C K ( µ ; ρ ) = C K ( µ ′ ; ρ ′ ) . • Integer: usually µ ′ � = µ means µ ′ � = µ mod n for some finite n . In an integer commitment scheme, µ ′ � = µ is taken over integers. Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 16

  17. Integer commitment schemes • Homomorphic: C K ( µ 1 + µ 2 ; ρ 1 + ρ 2 ) = C K ( µ 1 + µ 2 ; ρ 1 ) C K ( µ 1 + µ 2 ; ρ 2 ) • Easy to argue that c 1 = C K ( µ 1 ; · ) ∧ c 2 = C K ( µ 2 ; · ) ∧ c 3 = C K ( µ 1 µ 2 ; · ) this generalizes to an argument c 1 = C K ( µ 1 ; · ) ∧ c 2 = C K ( µ 2 ; · ) ∧ c 3 = C K ( f ( µ 1 , µ 2 ); · ) for for every f ∈ Z [ X ] Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 17

  18. Diophantine Arguments • Example: how to prove that c = C K ( µ ; · ) ∧ µ ≥ 0 : by Lagrange, ⇒ ( ∃ b ω 1 , ω 2 , ω 3 , ω 4 )[ µ = ω 2 1 + ω 2 2 + ω 2 3 + ω 2 µ ≥ 0 ⇐ 4 ] • Generally: demonstrate that you know ω , such that f ( µ ; ω ) = 0 Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 18

  19. Diophantine Arguments 1. Given µ , find such ω i (Algorithm: Rabin-Shallit, slightly improved by us) 2. Commit to all ω i , c i = C K ( ω i ; ρ i ) 3. Argue in ZK that c = C K ( µ ; ρ ) ∧ ( ∧ c i = C K ( ω i ; ρ i )) ∧ f ( µ ; ω ) = 0 where f ( µ ; ω ) = µ − � ω 2 i Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 19

  20. Diophantine Sets • We want to prove that µ ∈ S for some language S . By results of Matiyasevich etc, there exists an R S ∈ Z [ X ] , s.t. ( ∃ ω )[ R S ( µ ; ω ) = 0] ⇐ ⇒ µ ∈ S + We need that one can compute ω efficiently if it exists + ω must be polynomially short (in | µ | ) when µ ∈ S - On the other hand, ω may exist even if µ �∈ S , but in this case it must be very long (nonpolynomially long) • If such R S exists we say S ∈ PD Pedase Theory Day, 04.10.2003 On Diophantine Complexity and SZK Arguments, Helger Lipmaa 20

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