Robust Secret Sharing Schemes Against Local Adversaries Allison Bishop Lewko Valerio Pastro Columbia University April 2, 2015 Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 1 / 22 Secret Sharing (Informal) (Share, Rec) pair of algorithms: s Share / (s1 , . . . , sn ) /s Rec t-privacy: s1 , . . . , st ⇒ no info on s r -reconstructability: s1 , . . . , sr ⇒ s uniquely determined For threshold schemes: r = t + 1. Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 2 / 22 Example: Shamir Secret Sharing [Sha79] F field, public x1 , . . . , xn ∈ F. Shamir.Sharet (s): 1 2 3 4 pick uniform a1 , . . . , at ∈ F P define polynomial f (X ) := s + tj=1 aj X j ∈ F[X ] compute si ← f (xi ) output (s1 , . . . , sn ) Shamir.Rect (s1 , . . . , sn ): 1 Lagrange interpolation to recover f (X ) 2 output f (0) Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 3 / 22 Robust Secret Sharing – Standard Model (Share, Rec) Secret Sharing, (t, δ)-robust: for any Adv, s Share / (s1 , . . . , st , st+1 , . . . , sn ) _ (se1 ,...,set )=Adv(s1 ,...,st ) (se1 , . . . , set , st+1 , . . . , sn ) Rec / s0 Pr[s 0 6= s] ≤ δ Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 4 / 22 Robust Secret Sharing – with Local Adversaries (Share, Rec) Secret Sharing, locally (t, δ)-robust: for any Adv1 , . . . , Advt , s Share / (s1 , . . . , st , st+1 , . . . , sn ) _ se1 =Adv1 (s1 ),...,set =Advt (st ) (se1 , . . . , set , st+1 , . . . , sn ) Rec / s0 Pr[s 0 6= s] ≤ δ Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 5 / 22 Does Locality Make Sense? It captures the following: Pre-Game: Players talk to each other, set their actions Game: Players are given private inputs Players run protocol without revealing inputs to others Output of protocol is set Post-Game: Players talk to each other again, possibly revealing inputs Similar to collusion-free protocols [LMs05]. Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 6 / 22 Locality – Possible Scenarios Corrupt parties unwilling to coordinate (e.g. different goals) Corrupt parties oblivious about existence of each other Network with (independently) faulty channels Data is required to travel fast, coordination impossible ... Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 7 / 22 Locality – Related Work Interactive Proofs: Multi-prover interactive proofs: MIP=NEXP, [BFL91] (IP=PSPACE, [Sha92]) Multi-party Computation: Collusion-free protocols [LMs05, AKL+ 09, AKMZ12] Local UC [CV12] Leakage-resilient crypto: Split secret state and independent leakage [DP08] Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 8 / 22 Facts about Robust Secret Sharing Easy 0 n/3 Tricky n/2 Impossible t t < n/3: perfect robustness (δ = 0) no share size overhead (|si | = |s| =: m) e.g. Shamir share + Reed-Solomon decoding RS decodes up to (n − t)/2 > (3 · t − t)/2 = t errors n/3 ≤ t < n/2: tricky! no perfect robustness (δ = 2−k ) [Cev11] shares larger than secret (|si | > m) [Cev11] All of the above: independent of standard/local adv. model Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 9 / 22 The Tricky Case The trickiest case: n = 2 · t + 1. Analysis of |si |: m+k e + n) m + O(k lower bound [CSV93] best eff. construction [CFOR12] standard gap n / Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 10 / 22 The Tricky Case The trickiest case: n = 2 · t + 1. Analysis of |si |: m+k e + n) m + O(k lower bound [CSV93] best eff. construction [CFOR12] standard gap n / e m + k − 4 ∼ m + O(k) local adv. Our result: lower bound & eff. construction (essentially) match. , Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 10 / 22 Our Construction1 Previous Constructions Privacy: Shamir secret sharing, degree=t Robustness: one-time MAC, O(n) keys per player. ⇒ |si | inherent depends (at least) linearly on n Our Construction Privacy: Shamir secret sharing, degree=t Robustness: one-time MAC, one key only. 1 Conceptually simpler; thanks to Daniel Wichs for fruitful discussions. Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 11 / 22 In Detail Share(s): 1 2 3 4 5 sample MAC key z ∈ X (s1 , . . . , sn ) ← Shamir.Sharet (s) (z1 , . . . , zn ) ← Shamir.Share1 (z) ti ← MACz (si ) output Si = (si , zi , ti ) to Pi Rec(S1 , . . . , Sn ): 1 2 3 z ← RS.Rec1 (z1 , . . . , zn ) set i ∈ G if ti = MACz (si ) s ← Shamir.Rect (sG ) Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 12 / 22 Privacy – Proof Intuition Share(s): 1 2 3 4 5 t-privacy: sample MAC key z ∈ X (s1 , . . . , sn ) ← Shamir.Sharet (s) (z1 , . . . , zn ) ← Shamir.Share1 (z) ti ← MACz (si ) output Si = (si , zi , ti ) to Pi z uniform, independent of s, s1 , . . . , sn s1 , . . . , st give no info on s, (privacy of Shamir.Sharet ) t1 , . . . , tt functions only of z, s1 , . . . , st ⇒ S1 , . . . , St give no info on s Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 13 / 22 Robustness – Proof Intuition Rec(S1 , . . . , Sn ): 1 2 3 z ← RS.Rec1 (z1 , . . . , zn ) set i ∈ G if ti = MACz (si ) s ← Shamir.Rect (sG ) (t, δ)-robustness: z correct, because RS.Rec1 decodes up to (n − 1)/2 = (2t + 1 − 1)/2 = t errors Advi sees only si , zi , ti ⇒ no info on z (privacy of Shamir.Share1 ) MAC ε-secure ⇒ Pr[i ∈ G | sei 6= si ] ≤ ε ⇒ Pr[G ⊆ H ∪ P] ≥ 1 − t · ε ⇒ δ ≤t ·ε Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 14 / 22 Possible MAC and Overhead Analysis Remember: δ ≤ t · ε Assume: m = |s|, 2 · c = |z|, c = |ti |, m =2·d ·c MAC : (F2c )2 × F2m → F2c Pd l (a, b), (m1 , . . . , md ) 7→ l=1 a · ml + b. Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 15 / 22 Possible MAC and Overhead Analysis Remember: δ ≤ t · ε Assume: m = |s|, 2 · c = |z|, c = |ti |, m =2·d ·c MAC : (F2c )2 × F2m → F2c Pd l (a, b), (m1 , . . . , md ) 7→ l=1 a · ml + b. Fact: MAC is ε = d · 2−c -secure. Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 15 / 22 Possible MAC and Overhead Analysis Remember: δ ≤ t · ε Assume: m = |s|, 2 · c = |z|, c = |ti |, m =2·d ·c MAC : (F2c )2 × F2m → F2c Pd l (a, b), (m1 , . . . , md ) 7→ l=1 a · ml + b. Fact: MAC is ε = d · 2−c -secure. ⇒ construction is δ = t · ε = t · d · 2−c = t · m · 2−c−1 · c −1 -secure. Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 15 / 22 Possible MAC and Overhead Analysis Remember: δ ≤ t · ε Assume: m = |s|, 2 · c = |z|, c = |ti |, m =2·d ·c MAC : (F2c )2 × F2m → F2c Pd l (a, b), (m1 , . . . , md ) 7→ l=1 a · ml + b. Fact: MAC is ε = d · 2−c -secure. ⇒ construction is δ = t · ε = t · d · 2−c = t · m · 2−c−1 · c −1 -secure. e Set c = k + log(t · m) = O(k) ⇒ δ ≤ t · m · 2−k−log(t·m)−1 · c −1 ≤ 2−k e Overhead: |z| + |ti | = 2c + c = 3c = O(k) Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 15 / 22 Possible MAC and Overhead Analysis Remember: δ ≤ t · ε Assume: m = |s|, 2 · c = |z|, c = |ti |, m =2·d ·c MAC : (F2c )2 × F2m → F2c Pd l (a, b), (m1 , . . . , md ) 7→ l=1 a · ml + b. Fact: MAC is ε = d · 2−c -secure. ⇒ construction is δ = t · ε = t · d · 2−c = t · m · 2−c−1 · c −1 -secure. e Set c = k + log(t · m) = O(k) ⇒ δ ≤ t · m · 2−k−log(t·m)−1 · c −1 ≤ 2−k e Overhead: |z| + |ti | = 2c + c = 3c = O(k) , Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 15 / 22 Optimality of Construction Want to show: Scheme (t, 2−k )-robust against local advs ⇒ |si | ≥ m + k − 4 Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 16 / 22 Optimality of Construction Want to show: Scheme (t, 2−k )-robust against local advs ⇒ |si | ≥ m + k − 4 What we do: prove a stronger result! Scheme (t, 2−k )-robust against oblivious advs ⇒ |si | ≥ m + k − 4 local adv: oblivious adv: sei = Advi (si ) sei = Advi (∅) Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 16 / 22 Optimality of Construction Want to show: Scheme (t, 2−k )-robust against local advs ⇒ |si | ≥ m + k − 4 What we do: prove a stronger result! Scheme (t, 2−k )-robust against oblivious advs ⇒ |si | ≥ m + k − 4 local adv: oblivious adv: sei = Advi (si ) sei = Advi (∅) Proof structure: 1 define an oblivious attack 2 link success of attack with share size Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 16 / 22 The Attack Let st+1 be the shortest share. Specifications: “decide” whether to corrupt P1 , . . . , Pt (L) or Pt+2 , . . . , Pn (R) sample secret e s ← M, randomness e r ←R run (se1 , . . . , sen ) ← Share(e s, e r) if L, submit se1 , . . . , set ; if R, submit sg t+2 , . . . , sen Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 17 / 22 The Attack Let st+1 be the shortest share. Specifications: “decide” whether to corrupt P1 , . . . , Pt (L) or Pt+2 , . . . , Pn (R) sample secret e s ← M, randomness e r ←R run (se1 , . . . , sen ) ← Share(e s, e r) if L, submit se1 , . . . , set ; if R, submit sg t+2 , . . . , sen Intuition: hope that corrupt shares & st+1 consistent with dishonest secret. partial sharing of s L }| { z Rec s1 , . . . , st , st+1 , st+2 , . . . , sn = ? | {z } partial sharing of s R Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 17 / 22 The Decision Intuitively: find out whether L is more promising than R. Graph: (s L , r L ) connected to (s R , r R ) if: Share(s L , r L )t+1 = y = Share(s R , r R )t+1 , and s L 6= s R (s L , r L ) Lewko, Pastro (Columbia) (s R , r R ) RSSS & Loc Advs April 2, 2015 18 / 22 The Decision Intuitively: find out whether L is more promising than R. Graph: (s L , r L ) connected to (s R , r R ) if: Share(s L , r L )t+1 = y = Share(s R , r R )t+1 , and s L 6= s R Label edge with L (resp. R) if: R , . . . , s R ) 6= s R resp. 6= s L ) Rec(s1L , . . . , stL , y , st+2 n (s L , r L ) Lewko, Pastro (Columbia) (s R , r R ) RSSS & Loc Advs April 2, 2015 18 / 22 The Decision Intuitively: find out whether L is more promising than R. Graph: (s L , r L ) connected to (s R , r R ) if: Share(s L , r L )t+1 = y = Share(s R , r R )t+1 , and s L 6= s R Label edge with L (resp. R) if: R , . . . , s R ) 6= s R resp. 6= s L ) Rec(s1L , . . . , stL , y , st+2 n Decide L if #L-edges ≥ #R-edges. (s L , r L ) Lewko, Pastro (Columbia) (s R , r R ) RSSS & Loc Advs April 2, 2015 18 / 22 The Success (WLOG assume L) sL }| { z s1 , . . . , st , st+1 , st+2 , . . . , sn | {z } | {z } e s Lewko, Pastro (Columbia) sR RSSS & Loc Advs April 2, 2015 19 / 22 The Success (WLOG assume L) sL }| { z Rec s1 , . . . , st , st+1 , st+2 , . . . , sn 6= s R | {z } | {z } e s Lewko, Pastro (Columbia) sR RSSS & Loc Advs April 2, 2015 19 / 22 The Success (WLOG assume L) sL }| { z Rec s1 , . . . , st , st+1 , st+2 , . . . , sn 6= s R | {z } | {z } e s sR (s L , r L ) (e s, e r) Share(e s, e r ){1,...,t} = Share(s L , r L ){1,...,t} Lewko, Pastro (Columbia) (s R , r R ) Share(s L , r L )t+1 = Share(s R , r R )t+1 RSSS & Loc Advs April 2, 2015 19 / 22 The Success (WLOG assume L) sL }| { z Rec s1 , . . . , st , st+1 , st+2 , . . . , sn 6= s R | {z } | {z } e s sR (s L , r L ) (e s, e r) Share(e s, e r ){1,...,t} = Share(s L , r L ){1,...,t} (s R , r R ) Share(s L , r L )t+1 = Share(s R , r R )t+1 L δ = 2−k ≥ Pr (es ,er ,s R ,r R ) [∃(s L , r L ) | (e s, e r )—(s L , r L )—(s R , r R )] Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 19 / 22 Mass Distribution For a1 , . . . , at+1 , let Ba1 ,...,at+1 = {(s L , r L ) | Share(s L , r L ){1,...,t+1} = a1 , . . . , at+1 }, let Aa1 ,...,at+1 = {(e s, e r ) | Share(e s, e r ){1,...,t} = a1 , . . . , at }. Fact 1∗ : by reconstructability, (s 0 , r 0 ), (s 00 , r 00 ) ∈ Ba1 ,...,at+1 ⇒ s 0 = s 00 . (s L , r L ) (e s, e r) Share(e s, e r ){1,...,t} = Share(s L , r L ){1,...,t} Lewko, Pastro (Columbia) (s R , r R ) Share(s L , r L )t+1 = Share(s R , r R )t+1 RSSS & Loc Advs April 2, 2015 20 / 22 Mass Distribution For a1 , . . . , at+1 , let Ba1 ,...,at+1 = {(s L , r L ) | Share(s L , r L ){1,...,t+1} = a1 , . . . , at+1 }, let Aa1 ,...,at+1 = {(e s, e r ) | Share(e s, e r ){1,...,t} = a1 , . . . , at }. Fact 1∗ : by reconstructability, (s 0 , r 0 ), (s 00 , r 00 ) ∈ Ba1 ,...,at+1 ⇒ s 0 = s 00 . Fact 2: by privacy, |Aa1 ,...,at+1 | ≥ 2m · |Ba1 ,...,at+1 |. (s L , r L ) (e s, e r) Share(e s, e r ){1,...,t} = Share(s L , r L ){1,...,t} Lewko, Pastro (Columbia) (s R , r R ) Share(s L , r L )t+1 = Share(s R , r R )t+1 RSSS & Loc Advs April 2, 2015 20 / 22 Putting Things Together – Intuition Actual analysis needs more correcting factors (loss of ∼ 4 bits). L 2−k ≥ Pr (es ,er ,s R ,r R ) [∃(s L , r L ) | (e s, e r )—(s L , r L )—(s R , r R )] Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 21 / 22 Putting Things Together – Intuition Actual analysis needs more correcting factors (loss of ∼ 4 bits). L 2−k ≥ Pr (es ,er ,s R ,r R ) [∃(s L , r L ) | (e s, e r )—(s L , r L )—(s R , r R )] (Fact 1&2) L ≥ 2m · Pr (s L ,r L ,s R ,r R ) [(s L , r L )—(s R , r R )] Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 21 / 22 Putting Things Together – Intuition Actual analysis needs more correcting factors (loss of ∼ 4 bits). L 2−k ≥ Pr (es ,er ,s R ,r R ) [∃(s L , r L ) | (e s, e r )—(s L , r L )—(s R , r R )] (Fact 1&2) L ≥ 2m · Pr (s L ,r L ,s R ,r R ) [(s L , r L )—(s R , r R )] ≥ 2m−1 · Pr (s L ,r L ,s R ,r R ) [(s L , r L )—(s R , r R )] X ≥ 2m−1 · Pr (s L ,r L ,s R ,r R ) [Share(s L , r L ) = at+1 , Share(s R , r R ) = at+1 ] at+1 m−1 ≥2 · X Pr (s,r ) [Share(s, r ) = at+1 ]2 at+1 Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 21 / 22 Putting Things Together – Intuition Actual analysis needs more correcting factors (loss of ∼ 4 bits). L 2−k ≥ Pr (es ,er ,s R ,r R ) [∃(s L , r L ) | (e s, e r )—(s L , r L )—(s R , r R )] (Fact 1&2) L ≥ 2m · Pr (s L ,r L ,s R ,r R ) [(s L , r L )—(s R , r R )] ≥ 2m−1 · Pr (s L ,r L ,s R ,r R ) [(s L , r L )—(s R , r R )] X ≥ 2m−1 · Pr (s L ,r L ,s R ,r R ) [Share(s L , r L ) = at+1 , Share(s R , r R ) = at+1 ] at+1 m−1 ≥2 · X Pr (s,r ) [Share(s, r ) = at+1 ]2 (Cauchy-Schwarz) at+1 !2 m−1 ≥2 ·2 −|st+1 | X Pr (s,r ) [Share(s, r ) = at+1 ] · 1 at+1 = 2m−1 · 2−|st+1 | Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 21 / 22 Putting Things Together – Intuition Actual analysis needs more correcting factors (loss of ∼ 4 bits). L 2−k ≥ Pr (es ,er ,s R ,r R ) [∃(s L , r L ) | (e s, e r )—(s L , r L )—(s R , r R )] (Fact 1&2) L ≥ 2m · Pr (s L ,r L ,s R ,r R ) [(s L , r L )—(s R , r R )] ≥ 2m−1 · Pr (s L ,r L ,s R ,r R ) [(s L , r L )—(s R , r R )] X ≥ 2m−1 · Pr (s L ,r L ,s R ,r R ) [Share(s L , r L ) = at+1 , Share(s R , r R ) = at+1 ] at+1 m−1 ≥2 · X Pr (s,r ) [Share(s, r ) = at+1 ]2 (Cauchy-Schwarz) at+1 !2 m−1 ≥2 ·2 −|st+1 | X Pr (s,r ) [Share(s, r ) = at+1 ] · 1 at+1 = 2m−1 · 2−|st+1 | |st+1 | ≥ m + k − 1 Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 21 / 22 Putting Things Together – Intuition Actual analysis needs more correcting factors (loss of ∼ 4 bits). L 2−k ≥ Pr (es ,er ,s R ,r R ) [∃(s L , r L ) | (e s, e r )—(s L , r L )—(s R , r R )] (Fact 1&2) L ≥ 2m · Pr (s L ,r L ,s R ,r R ) [(s L , r L )—(s R , r R )] ≥ 2m−1 · Pr (s L ,r L ,s R ,r R ) [(s L , r L )—(s R , r R )] X ≥ 2m−1 · Pr (s L ,r L ,s R ,r R ) [Share(s L , r L ) = at+1 , Share(s R , r R ) = at+1 ] at+1 m−1 ≥2 · X Pr (s,r ) [Share(s, r ) = at+1 ]2 (Cauchy-Schwarz) at+1 !2 m−1 ≥2 ·2 −|st+1 | X Pr (s,r ) [Share(s, r ) = at+1 ] · 1 at+1 = 2m−1 · 2−|st+1 | |st+1 | ≥ m + k − 1 Lewko, Pastro (Columbia) RSSS & Loc Advs , April 2, 2015 21 / 22 Conclusion Robust SS with n = 2 · t + 1 players, eff. reconstruction. Share size: model standard NEW: local adv. Lewko, Pastro (Columbia) construction e + k) m + O(n lower bound e m + O(k) m+k −4 RSSS & Loc Advs m+k April 2, 2015 22 / 22 Conclusion Robust SS with n = 2 · t + 1 players, eff. reconstruction. Share size: model standard NEW: local adv. construction e + k) m + O(n lower bound e m + O(k) m+k −4 m+k Future: Locality in more complicated settings: I I info theoretic MPC: circumvent lower bounds? general MPC: more eff/practical protocols? standard RSSS: lower bound & construction matching? Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 22 / 22 Conclusion Robust SS with n = 2 · t + 1 players, eff. reconstruction. Share size: model standard NEW: local adv. construction e + k) m + O(n lower bound e m + O(k) m+k −4 m+k Future: Locality in more complicated settings: I I info theoretic MPC: circumvent lower bounds? general MPC: more eff/practical protocols? standard RSSS: lower bound & construction matching? Thanks! https://eprint.iacr.org/2014/909 Lewko, Pastro (Columbia) RSSS & Loc Advs April 2, 2015 22 / 22 Jo¨el Alwen, Jonathan Katz, Yehuda Lindell, Giuseppe Persiano, abhi shelat, and Ivan Visconti. Collusion-free multiparty computation in the mediated model. 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