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Cryptography for Unconditionally Secure Message Transmission in Networks Kaoru Kurosawa

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Popular Encryption Schemes Must share a secret-key Don’t share a secret-key ComputationalSKEPKE UnconditionalOne-time pad

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Does there exist ? Must share a secret-key Don’t share a secret-key ComputationalSKEPKE UnconditionalOne-time pad???

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Yes (1975) Wyner Wire-tap channel model (1984) Bennett and Brassard BB84 (1993) Dolev, Dwork, Waarts and Yung Network model

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In the model of DDWY Alice and Bob are a part of a network There are n channels between them Adversary can corrupt (observe and forge) at most t channels AliceBob

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Indeed, in Internet There are many channels between A and B No adversary can corrupt all the routers

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Dolev, Dwork, Waarts and Yung Showed that we can achieve (Perfect Privacy) Adversary learns no information on the secret message s (Perfect Reliability) Bob can receive s correctly (Adversary cannot forge s)

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There are many variants NetworkAdversarySecurity UndirectedThresholdPerfect DirectedGeneralAlmost perfect and etc.

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Many authors since DDWY Sayeed, Abu-Amara Franklin, Wright Kumar, Goudan, Srinatahn, Rangan, Narayanan, Patra, Choudhary Desmedt, Wang, Burmester, Yang Agarwal, Cramer, de Haan Garay, Ostrovsky, Fitzi, Vardhan Kurosawa, Suzuki

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This talk NetworkAdversarySecurity UndirectedThresholdPerfect DirectedGeneralAlmost perfect

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We begin with 1 st setting NetworkAdversarySecurity UndirectedThresholdPerfect DirectedGeneralAlmost perfect

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In an Undirected Network Each channel is two-way AliceBob

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1 Round Protocol Sender Receiver

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2 Round Protocol Sender Receiver Sender Receiver 1st 2nd

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PSMT denotes Perfectly Secure Message Transmission Scheme

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DDWY showed 1-round PSMT exists iff n ≧ 3t+1 2-round PSMT exists iff n ≧ 2t+1 where the adversary can corrupt t out of n channels.

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Let’s look at 1-round PSMT iff n ≧ 3t+1 2-round PSMTfor n = 2t+1 where an adversary can corrupt t out of n channels.

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2-round PSMT for n=2t+1 Larger than O(n)Lower bound O(n) Exp- time DDWY (1993) Poly- time Transmission rate

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2-round PSMT for n=2t+1 Larger than O(n)Lower bound O(n) Exp- time DDWY (1993) Poly- time Sayeed, Abu-Amara (1996) Transmission rate

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2-round PSMT for n=2t+1 Larger than O(n)Lower bound O(n) Srinathan, Narayan Rangan (2004) Exp- time DDWY (1993) Poly- time Sayeed, Abu-Amara (1996) Transmission rate

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2-round PSMT for n=2t+1 Larger than O(n)Lower bound O(n) Srinathan, Narayan Rangan (2004) Exp- time DDWY (1993)Agarwal, Cramer, de Haan (2006) Poly- time Sayeed, Abu-Amara (1996) Transmission rate

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2-round PSMT for n=2t+1 Larger than O(n)Lower bound O(n) Srinathan, Narayan Rangan (2004) Exp- time DDWY (1993)Agarwal, Cramer, de Haan (2006) Poly- time Sayeed, Abu-Amara (1996) Kurosawa, Suzuki (2008) Transmission rate

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Alice Bob s f(1) f(t) f(n) ・ ・ ・ ・ ・ ・ Suppose that Alice chooses a random f(x) such that f(0)=s and deg f(x) ≦ t

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Adversary Alice Bob s f(1) f(t) f(n) ・ ・ ・ ・ ・ ・ corrupts t channels.

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Perfect Privacy Is satisfied because this is a (t+1, n)-secret sharing scheme Hence the adverasry learns no information on s.

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Adversary Alice Bob s f(1) f(t) f(n) ・ ・ ・ ・ ・ ・ forges t channels. How about Perfect Reliability f(1)’ = f(1)+ e 1 f(t)’ = f(t)+ e t

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Perfect Reliability Bob can compute s if X=(f(1),…, f(n)) is a codeword of a t-error correcting code.

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X=(f(1),…, f(n)) has at most t zeros because deg f(x) ≦ t.

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X=(f(1),…, f(n)) has at most t zeros because deg f(x) ≦ t. Hence X has the minimum Hamming weight n-t.

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X=(f(1),…, f(n)) has at most t zeros because deg f(x) ≦ t. Hence X has the minimum Hamming weight n-t. Therefore the minimum Hamming distance of this linear code is d=n-t.

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If n=3t+1, the minimum Hamming distance is d = n – t = (3t+1) – t = 2t+1.

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If n=3t+1, the minimum Hamming distance is d=n – t = (3t+1) – t = 2t+1. Hence the receiver can correct t errors caused by the adversary.

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If n=3t+1, the minimum Hamming distance of C is d=n – t = (3t+1) – t = 2t+1. Hence the receiver can correct t errors caused by the adversary by using Berlekamp-Weltch algorithm

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If n=3t+1, the minimum Hamming distance is d=n – t = (3t+1) – t = 2t+1. Hence the receiver can correct t errors caused by the adversary. Thus perfect reliability is also satisfied.

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If n=3t+1, the minimum Hamming distance of C is d=n – t = (3t+1) – t = 2t+1. Hence the receiver can correct t errors caused by the adversary. Thus perfect reliability is satisfied. Therefore we can obtain a 1-round PSMT easily for n ≧ 3t+1

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If n=2t+1, however, the minimum Hamming distance is d = n - t = (2t+1) – t = t+1

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If n=2t+1, however, the minimum Hamming distance of C is d=n-t=(2t+1)-t= t+1 Hence the receiver can only detect t errors, but cannot correct them.

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If n=2t+1, however, the minimum Hamming distance of C is d=n-t=(2t+1)-t=t+1 Hence the receiver can only detect t errors, but cannot correct them. This is the main reason why PSMT for n=2t+1 is difficult.

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DDWY showed Exp-time 2-round PSMT Poly-time 3-round PSMT such that the transmission rate is O(n 5 ), where the transmission rate is defined as the total number of bits transmitted the size of the secrets

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Sayeed and Abu-Amara 2-round PSMT such that the transmission rate is O(n 3 )

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Srinathan, Narayan and Rangan the transmission rate ≧ n for any 2-round PSMT with n=2t+1. (CRYPTO 2004)

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Agarwal, Cramer and de Haan ・ Exp-time 2-round PSMT such that the trans. rate is O(n). (CRYPTO 2006)

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Kurosawa and Suzuki ・ Poly-time 2-round PSMT such that the trans. rate is O(n). at Eurocrypt 2008 Final version: IEEE Trans. on IT, 2009

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Our Idea What is a difference between error correction and PSMT ?

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What is a difference If the sender sends a single codeword, then adversary causes t errors randomly.

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What is a difference If the sender sends a single codeword, then adversary causes t errors randomly. Hence there is no difference.

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However If the sender sends many codewords X 1, …, X m, then the errors are not totally random because the errors always occur at the same t (or less) places !

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Our Observation Suppose that the receiver received Y 1 =X 1 + E 1, …, Y m =X m + E m, where E 1, …, E m are error vectors

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Our Observation Let E = [E 1, …, E m ]. Then dim E ≦ t because the errors always occur at the same t (or less) places !

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But The receiver does not know the error vectors E 1, …, E m

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Our Contribution We introduced a notion of pseudo-dimension pseudo-basis,

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Let Y= {Y 1, …, Y m } Let E = [E 1, …, E m ]. If Y has Pseudo dim kthen E has dim k If Y has a Pseudo basis {Y j1, …, Y jk } then E has a basis {E j1, …, E jk } Intuition

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Our Contribution We then showed a poly-time algorithm which finds pseudo-basis and pseudo-dimension from Y={Y 1, …, Y m }.

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More Observation For example, E 1 =(1,0, …, 0), E 2 =(1,1,0, …, 0), … E t =(1,…,1,0, …, 0), is a basis of E.

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More Observation E 1 =(1,0, …, 0), NonZero(E 1 )={1} E 2 =(1,1,0, …, 0), NonZero(E 2 )={1,2} … E t =(1,…,1,0, …, 0), NonZero(E t )={1, …, t}

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More Observation E 1 =(1,0, …, 0), NonZero(E 1 )={1} E 2 =(1,1,0, …, 0), NonZero(E 2 )={1,2} … E t =(1,…,1,0, …, 0), NonZero(E t )={1, …, t} Define FORGED = U NonZero(E i ) basis

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More Observation E 1 =(1,0, …, 0), NonZero(E 1 )={1} E 2 =(1,1,0, …, 0), NonZero(E 2 )={2} … E t =(1, …, 1, 0, …, 0), NonZero(E t )= {t} Define FORGED ≡ U basis NonZero(E i ) Then FORGED = {all forged channels}

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Our basic 2-round PSMT Let t = 1 and n = 2t+1 = 3 That is, Adversary can corrupt 1 out of 3 channels

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It consists of 3 phases Encryption phase Error detection phase Decryption phase We run them in parallel

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Encryption phase (1 st R) R sends random f 1 (x), f 2 (x) and f 3 (x) with deg f i (x) ≦ 1 as follows f 1 (x) f 2 (x) f 3 (x) S R

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Encryption phase (1 st R) S receives f 1 ’(x), f 2 ’(x) and f 3 ’(x) f 1 ’(x) f 2 ’(x) f 3 ’(x) S

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Encryption phase (2 nd R) S broadcasts c = s + f 1 ’(1) +f 2 ’(2) + f 3 ’(3) c c c S R

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Encryption phase (2 nd R) R can receive c correctly by taking majority vote because at most 1 channel is corrupted c c c’ R

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Error detection phase (1 st R) R sends X 1, X 2, X 3 such that R f 2 (1) f 2 (2) f 2 (3) X 2 || f 1 (1) f 1 (2) f 1 (3) X 1 || f 3 (1) f 3 (2) f 3 (3) X 3 ||

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S receives S f 2 (1)’ f 2 (2)’ f 2 (3)’ Y 2 || f 1 (1)’ f 1 (2)’ f 1 (3)’ Y 1 || f 3 (1)’ f 3 (2)’ f 3 (3)’ Y 3 ||

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From {Y 1, Y 2, Y 3 } S f 2 (1)’ f 2 (2)’ f 2 (3)’ Y2Y2 f 1 (1)’ f 1 (2)’ f 1 (3)’ Y1Y1 f 3 (1)’ f 3 (2)’ f 3 (3)’ Y3Y3 S computes the psudo-dimension k and a pseudo-basis Λ by using the proposed algorithm

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For example S f 2 (1)’ f 2 (2)’ f 2 (3)’ Y2Y2 f 1 (1)’ f 1 (2)’ f 1 (3)’ Y1Y1 f 3 (1)’ f 3 (2)’ f 3 (3)’ Y3Y3 S computes the psudo-dimension k=1 and a pseudo-basis Λ={Y 1 }

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S broadcasts S f 2 (1)’ f 2 (2)’ f 2 (3)’ Y2Y2 f 1 (1)’ f 1 (2)’ f 1 (3)’ Y1Y1 f 3 (1)’ f 3 (2)’ f 3 (3)’ Y3Y3 S k=1, Λ={Y 1 }

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R sent X 1 and received Y 1 =X 1 +E 1 R f 2 (1) f 2 (2) f 2 (3) X2X2 f 1 (1) f 1 (2) f 1 (3) X1X1 f 3 (1) f 3 (2) f 3 (3) X3X3 R k=1, Λ={Y 1 }

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Hence R can compute E 1 =Y 1 - X 1 R f 2 (1) f 2 (2) f 2 (3) X2X2 f 1 (1) f 1 (2) f 1 (3) X1X1 f 3 (1) f 3 (2) f 3 (3) X3X3 k=1, Λ={Y 1 } R

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Suppose that E 1 =Y 1 - X 1 =[0,0,e 3 ] T R f 2 (1) f 2 (2) f 2 (3) X2X2 f 1 (1) f 1 (2) f 1 (3) X1X1 f 3 (1) f 3 (2) f 3 (3) X3X3 k=1, Λ={Y 1 } R

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Suppose that E 1 =[0,0,e 3 ] T Then R sees that channel 3 is corrupted R f 2 (1) f 2 (2) f 2 (3) f 1 (1) f 1 (2) f 1 (3) f 3 (1) f 3 (2) f 3 (3) X1X1 X2X2 X3X3 Adversary

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f 1 (x) f 2 (x) f 3 (x) S R What happened ? X1X1 X2X2 X3X3

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Adversary corrupted channel 3 f 1 (x) f 2 (x) f 3 (x) S R What happened ? Adversary X1X1 X2X2 X3X3

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Adversary corrupted channel 3 S broadcast c and Y 1 =pseudo-basis f 1 (x) f 2 (x) f 3 (x) S R S c, Y 1 What happened ? Adversary X1X1 X2X2 X3X3

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Adversary corrupted channel 3 S broadcast c and Y 1 =pseudo-basis Then R found that channel 3 was corrupted f 1 (x) f 2 (x) f 3 (x) S R S c, Y 1 What happened ? Adversary X1X1 X2X2 X3X3

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Adversary observed f 3 (x) and Y 1 ≃ f 1 (x) f 1 (x) f 2 (x) f 3 (x) S R S c, Y 1 In particular Adversary X1X1 X2X2 X3X3

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Adversary observed f 3 (x) and Y 1 ≃ f 1 (x) But f 2 (2) is kept hidden f 1 (x) f 2 (x) f 3 (x) S R S c, Y 1 In particular Adversary X1X1 X2X2 X3X3 f 2 (2)

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R can find the corrupted channel keeping f 2 (2) secret f 1 (x) f 2 (x) f 3 (x) S R S c, Y 1 In other words Adversary X1X1 X2X2 X3X3 f 2 (2)

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If R sends f 1 (x), ⋯, f 6 (x), then R can find the corrupted channel keeping f 2 (2), f 4 (1), f 5 (2) secret f 1 (x), f 4 (x) f 2 (x), f 5 (x) f 3 (x), f 6 (x) S R S Y1Y1 Adversary

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If R sends f 1 (x), ⋯, f 6 (x), then R can find the corrupted channel keeping f 2 (2), f 4 (1), f 5 (2) secret Only Y 1 is broadcast as a pseudo-basis f 1 (x), f 4 (x) f 2 (x), f 5 (x) f 3 (x), f 6 (x) S R S Y1Y1 Adversary

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Going back to our basic scheme let’s look at f 3 (x) R f 3 (1) f 3 (2) f 3 (3) f 3 (x)

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R knows that S y 1 =f 3 (1) y 2 =f 3 (2) f 3 ’(x), y 3 S received

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y 1 =f 3 (1) S y 2 =f 3 (2) f 3 ’(x), y 3 S Δ 1 = f 3 ’(1) - y 1 Δ 2 = f 3 ’(2) - y 2 Δ 3 = f 3 ’(3) - y 3 S broadcasts Decryption phase

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y 1 =f 3 (1) S y 2 =f 3 (2) y3y3 S Δ 1 = f 3 ’(1) -y 1 Δ 2 = f 3 ’(2) -y 2 Δ 3 = f 3 ’(3)-y 3 From these 2 equations, R can compute f 3 ’(1) =Δ 1 +f 3 (1) R

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y 1 =f 3 (1) S y 2 =f 3 (2) y3y3 S Δ 1 = f 3 ’(1) -y 1 Δ 2 = f 3 ’(2) -y 2 Δ 3 = f 3 ’(3)-y 3 From these 2 equations, R can compute f 3 ’(2) =Δ 2 +f 3 (2) R

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y 1 =f 3 (1) S y 2 =f 3 (2) y3y3 S Δ 1 = f 3 ’(1) -y 1 Δ 2 = f 3 ’(2) -y 2 Δ 3 = f 3 ’(3)-y 3 Then R can obtain f 3 ’(x) by applying Lagrange formula to f 3 ’(1) and f 3 ’(2) R

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Perfect Reliability R can obtain f 1 ’(x) and f 2 ’(x) similarly

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Perfect Reliability R can obtain f 1 ’(x) and f 2 ’(x) similarly Remember that R received c = s + f 1 ’(1) + f 2 ’(2) + f 3 ’(3)

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Perfect Reliability R can obtain f 1 ’(x) and f 2 ’(x) similarly Remember that R received c = s + f 1 ’(1) + f 2 ’(2) + f 3 ’(3) Now R can compute s

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Perfect Reliability R can obtain f 1 ’(x) and f 2 ’(x) similarly Remember that R received c = s + f 1 ’(1) + f 2 ’(2) + f 3 ’(3) Now R can compute s Therefore perfect reliability is satisfied

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Perfect Privacy S broadcasts c = s + f 1 ’(1) + f 2 ’(2) + f 3 ’(3)

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Perfect Privacy S broadcasts c = s + f 1 ’(1) + f 2 ’(2) + f 3 ’(3) Y 1 is broadcast by S as a pseudo-basis

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Perfect Privacy S broadcasts c = s + f 1 ’(1) + f 2 ’(2) + f 3 ’(3) Y 1 is broadcast by S as a pseudo-basis Adversary observed f 3 ’(x)

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Perfect Privacy S broadcasts c = s + f 1 ’(1) + f 2 ’(2) + f 3 ’(3) Y 1 is broadcast by S as a pseudo-basis Adversary observed f 3 ’(x) But she has no info. on f 2 ’(2)= f 2 (2)

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Perfect Privacy S broadcasts c = s + f 1 ’(1) + f 2 ’(2) + f 3 ’(3) Y 1 is broadcast by S as a pseudo-basis Adversary observed f 3 ’(x) But she has no info. on f 2 ’(2) = f 2 (2) Hence perfect privacy is also satisfied

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Final scheme R sends many f i (x) in parallel S uses “generalized broadcast” Then we can obtain the transmission rate = O(n)

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Now what is pseudo-basis Let C be a linear code such that the codewords are (f(1), ⋯, f(n)), where deg f(x) ≦ t That is, C={ (f(1), ⋯, f(n)) | deg f(x) ≦ t }

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We write Y 1 = Y 2 mod C if Y 1 - Y 2 ∈ C

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We write Y 1 = Y 2 mod C if Y 1 - Y 2 ∈ C In particular, if Y=X+E, then Y=E mod C

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Linearly pseudo-expressed We say that Y 0 is linearly pseudo-expressed by {Y 1, ⋯, Y k } if Y 0 = a 1 Y 1 + ⋯ + a k Y k mod C for some (a 1, ⋯, a k )

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Pseudo Span Let Λ ⊆ Y = {Y 1, ⋯, Y m }, We say that Λ pseudo spans Y if each Y i is linearly pseudo-expressed by Λ

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Pseudo-Basis We say that Λ is a pseudo-basis of Y if it is a minimum set which pseudo-spans Y

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Pseudo-Dimension Suppose that Λ is a pseudo-basis of Y We say that k=|Λ| is the pseudo-dimension of Y

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Admissible Error Vector Set We say that {E 1, ⋯,E m } is an admissible error vector set of Y={Y 1, ⋯,Y m } if E i =Y i mod C for all i |U NonZero(E i )| ≦ t i

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Theorem Let {E 1, ⋯,E m } be an admissible error vector set of Y= {Y 1, ⋯,Y m } Y= {Y 1, …, Y m }E = [E 1, …, E m ]. Y has Pseudo dim kiff E has dim k Y has a Pseudo basis {Y j1, …, Y jk } iff E has a basis {E j1, …, E jk }

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Corollary Let {E 1, ⋯,E m } be the real error vector set caused by the adversary Y= {Y 1, …, Y m }E = [E 1, …, E m ]. If Y has Pseudo dim kthen E has dim k If Y has a Pseudo basis {Y j1, …, Y jk } then E has a basis {E j1, …, E jk }

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Next how to check linearly pseudo-expressed Y 3 –(a 1 Y 1 +a 2 Y 2 ) = 0 mod C This equation means LHS = some codeword (f(1), ⋯, f(n))

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First construct f (a1,a2) (x) by applying Lagrange formula to the first t+1 elements of Y 3 – (a 1 Y 1 +a 2 Y 2 ) like this f (a1,a2) (1) = y 3,1 ー (a 1 y 1,1 + a 2 y 2,1 ) ⋮ f (a1,a2) (t+1) = y 3.t+1 ー (a 1 y 1,t+1 + a 2 y 2,t+1 )

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Next check if f (a1,a2) (x) is consistent with the remaining elements of Y 3 – (a 1 Y 1 +a 2 Y 2 ) for some (a 1,a 2 ) f (a1,a2) (t+2) = y 3,t+2 ー (a 1 y 1,t+2 + a 2 y 2,t+2 ) ⋮ f (a1,a2) (n) = y 3,n ー (a 1 y 1,n + a 2 y 2,n )

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This can be done easily By checking if the following linear equations has a solution (a 1,a 2 ) f (a1,a2) (t+2) = y 3,t+2 ー (a 1 y 1,t+2 + a 2 y 2,t+2 ) ⋮ f (a1,a2) (n) = y 3,n ー (a 1 y 1,n + a 2 y 2,n )

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If yes, then Y 3 is linearly pseudo-expressed by {Y 1,Y 2 }

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Algorithm for finding pseudo-basis Input: Y={Y 1, …, Y m } Let Λ=empty For i=1 to m, do: While |Λ|

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2-round PSMT for n=2t+1 Larger than O(n)Lower bound O(n) Srinathan, Narayan Rangan (2004) Exp- time DDWY (1993)Agarwal, Cramer, de Haan (2006) Poly- time Sayeed, Abu-Amara (1996) Kurosawa, Suzuki (2008) Transmission rate

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For the details ・ Please look at the paper Truly Efficient 2-Round Perfectly Secure Message Transmission Scheme Kurosawa and Suzuki Preliminary: Eurocrypt 2008 Final: IEEE Trans. on IT, 2009

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Patra, Choudhary and Rangan Used pseudo-basis to construct Communication optimal 3 and 6 round PSMT in directed networks (ICDCN 2010) 3-round communication optimal PSMT tolerating mobile mixed adversary (PODC 2010)

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Yang and Desmedt used pseudo-basis to construct 2-round PSMT for Q 2 adversary structure (Asiacrypt 2010)

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Open Problem (1) Can we apply pseudo-basis to another problems ?

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Open Problem (2) The transmission rate is the total number of bits transmitted the size of the secrets

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Open Problem (2) In our PSMT the total number of bits transmitted = O(n 3 ) the size of the secrets = O(n 2 ) to achieve the transmission rate = O(n)

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Open Problem (2) In our PSMT the total number of bits transmitted = O(n 3 ) the size of the secrets = O(n 2 ) to achieve the transmission rate = O(n) What is a lower bound on the communication complexity to achieve our goal ?

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Next 2nd setting NetworkAdversarySecurity UndirectedThresholdPerfect DirectedGeneralAlmost perfect

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Desmedt et at. Threshold adversaries are not realistic when dealing with computer viruses, such as the I LOVE YOU virus and the Internet virus/worm that only spread to Windows, respectively Unix.

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{1,2,3} use Windows SR3 2 1 4 5 SenderReceiver

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{3,4} use UNIX SR3 2 1 4 5 SenderReceiver

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{1,5} use TRON SR3 2 1 4 5 SenderReceiver

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Adversary Structure Adversary can corrupt B 1 ={1,2,3} or B 2 ={3,4} or B 3 ={1,5}. Let Γ={B 1, B 2, B 3 } Such Γ is called an adversary structure.

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Hirt and Maurer Introduced adversary structure in the context of multiparty protocols They generalized n ≧ 2t+1 to Q 2 adversary structure n ≧ 3t+1 to Q 3 adversary structure

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Γ satisfies Q 2 If B i ⋃ B j ≠ {1, ⋯, n} for any B i, B j ∊ Γ

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Γ satisfies Q 3 If B i ⋃ B j ⋃ B k ≠ {1, ⋯, n} for any B i, B j, B k ∊ Γ

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PSMT for General Adversary 2002 Kumar, Goudan, Srinatahn, Rangan Many round PSMT for Q 2 2005 Desmedt, Wang, Burmester Exp-time 1-round PSMT for Q 3 2009 Kurosawa Poly-time 1-round PSMT for Q 3 2010 Yang, Desmedt Poly-time 2-round PSMT for Q 2

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I will explain 2002 Kumar, Goudan, Srinatahn, Rangan Many round PSMT for Q 2 2005 Desmedt, Wang, Burmester Exp-time 1-round PSMT for Q 3 2009 Kurosawa Poly-time 1-round PSMT for Q 3 2010 Yang, Desmedt 2-round PSMT for Q 2

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Monotone We say that Γ is monotone if B ∈ Γ and B’ ⊂ B, then B’ ∈ Γ For example. if an adversary can corrupt B={1,2,3}, then she can corrupt B’={1,2} clearly. In what follows, we assume that Γ is monotone

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Proposition For any monotone adversary structure Γ, there exists a linear secret sharing scheme such that if B ∈ Γ, then B has no information on s If A ∉ Γ, then A can reconstruct s

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Proposition For any monotone adversary structure Γ, there exists a (linear) secret sharing scheme such that if B ∈ Γ, then B has no information on s If A ∉ Γ, then A can reconstruct s We call such a scheme a secret sharing scheme for Γ

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What is a difference between Shamir’s threshold secret sharing scheme and general secret sharing schemes ?

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Secret Sharing Scheme Sharing phase: For a secret s, Dealer computes a share vector V=(v 1, ⋯, v n ), and gives v i to player P i

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Secret Sharing Scheme Reconstruction phase: Suppose that some subset of players B ∈ Γ open forged shares Let Y=V+E where V is a share vector and E is an error vector

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In Shamir’s threshold SS, If n ≧ 3t+1, then Berlekamp-Weltch algorithm can correct t erros in Y=V+E in poly-time

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For Q 3 adversary structure, no secret sharing scheme was known such that s can be reconstructed in poly-time from Y (=V+E) This is the reason why the construction of 1-round PSMT for Q 3 is difficult

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I constructed A secret sharing scheme for Q 3 such that s can be reconstructed from Y (=V+E) in poly-time

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Proposed construction For a Q 3 -adversary structure Γ, let LSSS be a linear secret sharing scheme such that if B ∈ Γ, then B has no information on s If A ∉ Γ, then A can reconstruct s

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Step 1 LSSS v1 ⋮vnv1 ⋮vn s r0r0

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Step 2 LSSS u 11 ⋮ u 1n v1v1 r1r1 LSSS v1 ⋮vnv1 ⋮vn s r0r0

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Dealer distributes P1P1 (v 1, r 1 ) u 11 P2P2 u 12 ⋮⋮ PnPn u 1n

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Similarly LSSS u 21 ⋮ u 2n v2v2 r2r2 LSSS v1v2 ⋮vnv1v2 ⋮vn s r0r0

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Dealer distributes P1P1 (v 1, r 1 ) u 11 u 21 P2P2 u 12 (v 2, r 2 ) u 22 ⋮⋮⋮ PnPn u 1n u 2n

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And so on. P1P1 (v 1, r 1 ) u 11 u 21 ⋯ u n1 P2P2 u 12 (v 2, r 2 ) u 22 ⋯ u n2 ⋮⋮⋮⋯⋮ PnPn u 1n u 2n ⋯ (v n, r n ) u nn

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In the Reconstruction phase Suppose that some subset of players B ∈ Γ open forged shares We will show a poly-time algorithm which can reconstruct s

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Suppose that P1P1 (v 1, r 1 ) u 11 u 21 ⋯ u n1 P2P2 u 12 (v 2, r 2 ) u 22 ⋯ u n2 ⋮⋮⋮⋯⋮ PnPn u 1n u 2n ⋯ (v n, r n ) u nn Each player opened blue shares

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Decoding algorithm: Step 1 LSSS u 11 ⋮ u 1n v1v1 r1r1 Run the LSSS on input (v 1, r 1 ) to generate red shares

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Then compare the red shares with the blue shares LSSS u 11 ⋮ u 1n v1v1 r1r1 u 11 ⋮ u 1n Accept v 1 if { j | u 1j ≠ u 1j } ∈ Γ ≠ =

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Similarly LSSS u i1 ⋮ u in vivi riri Run the LSSS on input (v i, r i ) to generate red shares

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Compare the red shares with the blue shares LSSS u i1 ⋮ u in vivi riri u i1 ⋮ u in Accept v i if { j | u ij ≠ u ij } ∈ Γ

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Decoding algorithm: Step 2 Finally apply the reconstruction alorithm of the LSSS to {acepted v i }, and reconstruct s

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That is, Reconstruction algorithm of LSSS { accepted v i } s

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Theorem Proposed scheme is a secret sharing scheme for a Q 3 adversary structure Γ

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Theorem Proposed scheme is a secret sharing scheme for a Q 3 adverary structure Γ Even if some B ∈ Γ open forged shares, the decoding algorithm can reconstruct s in poly-time in the size of the LSSS (which is the total size of the shares)

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Application to PSMT We can construct a 1-round PSMT for any Q 3 -adverary structure which runs in poly-time in the size of the underlying LSSS

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Proposed PSMT Channel 1 (v 1, r 1 ) u 11 u 21 ⋯ u n1 Channel 2 u 12 (v 2, r 2 ) u 22 ⋯ u n2 ⋮⋮⋮⋯⋮ Channel n u 1n u 2n ⋯ (v n, r n ) u nn

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For Q 3 adversary structure 2005 Desmedt, Wang, Burmester Exp-time 1-round PSMT 2009 Kurosawa Poly-time 1-round PSMT

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For the details Please look at the paper ePrint 2009/263 General Error Decodable Secret Sharing Scheme and Its Application Kaoru Kurosawa

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Summary Poly-time 2-round PSMT for n=2t+1 with the trans. rate O(n) Poly-time 1-round PSMT for Q 3 adversary structure

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Open Problems It seems that there are many open problems in this area because there are many variants of this model, some parameters to be optimized.

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THANK YOU !!

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Brief Announcement on our new result ePrint 2010/609 The Round Complexity of General VSS Ashish Choudhary Kaoru Kurosawa Arpita Patra

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Verifiable Secret Sharing (VSS) Is a fundamental building block in many distributed cryptographic protocols. In this model, Adversary can corrupt not only some subset of players but also the dealer

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Even though, A unique secret must be reconstructed in the reconstruction phase no matter how malicious players behave.

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STOC 2001 Gennaro, Ishai, Kushilevitz and Rabin showed that 2 round VSS is possible iff n ≧ 4t+1 3 round VSS is possible iff n ≧ 3t+1

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TCC 2006 Fitzi, Garay, Gollakota, Rangan and Srinathan Constructed a poly-time 3-round VSS for n ≧ 3t+1

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We consider general adversary Our resultPrevious 2-round VSSiff Γ is Q 4 n ≧ 4t+1 3-round VSSiff Γ is Q 3 n ≧ 3t+1

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As a special case of our VSS We can obtain a more efficient 3-round VSS than the VSS of Fitzi et al. for n = 3t+1 The communication complexity of the reconstruction phase is reduced from O(n 3 ) to O(n 2 )

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Further We point out a flaw in the reconstruction phase of VSS of Fitzi et al., and show how to fix it.

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For the details Please look at the paper ePrint 2010/609 The Round Complexity of General VSS Ashish Choudhary Kaoru Kurosawa Arpita Patra

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THANK YOU, AGAIN !!

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1 Introduction to Quantum Information Processing CS 467 / CS 667 Phys 467 / Phys 767 C&O 481 / C&O 681 Richard Cleve DC 3524 Course.

1 Introduction to Quantum Information Processing CS 467 / CS 667 Phys 467 / Phys 767 C&O 481 / C&O 681 Richard Cleve DC 3524 Course.

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