Computational Complexity

Chailloux, André, Dragos Florin Ciocan, Iordanis Kerenidis, and Salil Vadhan. “Interactive and noninteractive zero knowledge are equivalent in the help model.” In Proceedings of the Third Theory of Cryptography Conference (TCC '08), 4948:501-534. Springer-Verlag, Lecture Notes in Computer Science, 2008. Publisher's VersionAbstract

Version History: 

  • Preliminary versions of this work previously appeared on the Cryptology ePrint Archive and in the second author’s undergraduate thesis.
  • Chailloux, A., Kerenidis, I.: The role of help in classical and quantum zero-knowledge. Cryptology ePrint Archive, Report 2007/421 (2007),
  • Ciocan, D.F., Vadhan, S.: Interactive and noninteractive zero knowledge coincide in the help model. Cryptology ePrint Archive, Report 2007/389 (2007),
  • Ciocan, D.: Constructions and characterizations of non-interactive zero-knowledge. Undergradute thesis, Harvard University (2007) 

We show that interactive and noninteractive zero-knowledge are equivalent in the ‘help model’ of Ben-Or and Gutfreund (J. Cryptology, 2003). In this model, the shared reference string is generated by a probabilistic polynomial-time dealer who is given access to the statement to be proven. Our results do not rely on any unproven complexity assumptions and hold for statistical zero knowledge, for computational zero knowledge restricted to AM, and for quantum zero knowledge when the help is a pure quantum state.

Ong, Shien Jin, and Salil Vadhan. “An equivalence between zero knowledge and commitments.” In R. Canetti, editor, Proceedings of the Third Theory of Cryptography Conference (TCC ‘08), 4948:482-500. Springer Verlag, Lecture Notes in Computer Science, 2008. Publisher's VersionAbstract

We show that a language in NP has a zero-knowledge protocol if and only if the language has an “instance-dependent” commitment scheme. An instance-dependent commitment schemes for a given language is a commitment scheme that can depend on an instance of the language, and where the hiding and binding properties are required to hold only on the yes and no instances of the language, respectively.

The novel direction is the only if direction. Thus, we confirm the widely held belief that commitments are not only sufficient for zero knowledge protocols, but necessary as well. Previous results of this type either held only for restricted types of protocols or languages, or used nonstandard relaxations of (instance-dependent) commitment schemes.

Gutfreund, Dan, and Salil Vadhan. “Limitations on hardness vs. randomness under uniform reductions.” In Proceedings of the 12th International Workshop on Randomization and Computation (RANDOM ‘08), Lecture Notes in Computer Science, 5171:469-482. Springer-Verlag, 2008. Publisher's VersionAbstract

We consider (uniform) reductions from computing a function \({f}\) to the task of distinguishing the output of some pseudorandom generator \({G}\) from uniform. Impagliazzo and Wigderson [10] and Trevisan and Vadhan [24] exhibited such reductions for every function \({f}\) in PSPACE. Moreover, their reductions are “black box,” showing how to use any distinguisher \({T}\), given as oracle, in order to compute \({f}\) (regardless of the complexity of \({T}\) ). The reductions are also adaptive, but with the restriction that queries of the same length do not occur in different levels of adaptivity. Impagliazzo and Wigderson [10] also exhibited such reductions for every function \({f}\) in EXP, but those reductions are not black-box, because they only work when the oracle \({T}\) is computable by small circuits.

Our main results are that:

– Nonadaptive black-box reductions as above can only exist for functions \({f}\) in BPPNP (and thus are unlikely to exist for all of PSPACE).

– Adaptive black-box reductions, with the same restriction on the adaptivity as above, can only exist for functions \({f}\) in PSPACE (and thus are unlikely to exist for all of EXP).

Beyond shedding light on proof techniques in the area of hardness vs. randomness, our results (together with [10,24]) can be viewed in a more general context as identifying techniques that overcome limitations of black-box reductions, which may be useful elsewhere in complexity theory (and the foundations of cryptography).

Bogdanov, Andrej, Elchanan Mossel, and Salil Vadhan. “The complexity of distinguishing Markov random fields.” In Proceedings of the 12th International Workshop on Randomization and Computation (RANDOM ‘08), Lecture Notes in Computer Science, 5171:331-342. Springer-Verlag, 2008. Publisher's VersionAbstract

Markov random fields are often used to model high dimensional distributions in a number of applied areas. A number of recent papers have studied the problem of reconstructing a dependency graph of bounded degree from independent samples from the Markov random field. These results require observing samples of the distribution at all nodes of the graph. It was heuristically recognized that the problem of reconstructing the model where there are hidden variables (some of the variables are not observed) is much harder.

Here we prove that the problem of reconstructing bounded-degree models with hidden nodes is hard. Specifically, we show that unless NP = RP,

  • It is impossible to decide in randomized polynomial time if two mod- els generate distributions whose statistical distance is at most 1/3 or at least 2/3.
  • Given two generating models whose statistical distance is promised to be at least 1/3, and oracle access to independent samples from one of the models, it is impossible to decide in randomized polynomial time which of the two samples is consistent with the model.

The second problem remains hard even if the samples are generated efficiently, albeit under a stronger assumption.

Reingold, Omer, Luca Trevisan, Madhur Tulsiani, and Salil Vadhan. “Dense subsets of pseudorandom sets.” In Proceedings of the 49th Annual IEEE Symposium on Foundations of Computer Science (FOCS ‘08), 76-85. IEEE, 2008. Publisher's VersionAbstract
A theorem of Green, Tao, and Ziegler can be stated (roughly) as follows: if R is a pseudorandom set, and D is a dense subset of R, then D may be modeled by a set M that is dense in the entire domain such that D and M are indistinguishable. (The precise statement refers to "measures" or distributions rather than sets.) The proof of this theorem is very general, and it applies to notions of pseudo-randomness and indistinguishability defined in terms of any family of distinguishers with some mild closure properties. The proof proceeds via iterative partitioning and an energy increment argument, in the spirit of the proof of the weak Szemeredi regularity lemma. The "reduction" involved in the proof has exponential complexity in the distinguishing probability. We present a new proof inspired by Nisan's proof of Impagliazzo's hardcore set theorem. The reduction in our proof has polynomial complexity in the distinguishing probability and provides a new characterization of the notion of "pseudoentropy" of a distribution. A proof similar to ours has also been independently discovered by Gowers [2]. We also follow the connection between the two theorems and obtain a new proof of Impagliazzo's hardcore set theorem via iterative partitioning and energy increment. While our reduction has exponential complexity in some parameters, it has the advantage that the hardcore set is efficiently recognizable.
Ong, Shien Jin, and Salil Vadhan. “Zero knowledge and soundness are symmetric.” In Advances in Cryptology–EUROCRYPT '07, 4515:187-209. Barcelona, Spain: Springer Verlag, Lecture Notes in Computer Science, M. Naor, ed. 2007. Publisher's VersionAbstract

Version History: Recipient of Best Paper Award. Preliminary version posted on ECCC as TR06-139, November 2006.

We give a complexity-theoretic characterization of the class of problems in NP having zero-knowledge argument systems. This characterization is symmetric in its treatment of the zero knowledge and the soundness conditions, and thus we deduce that the class of problems in NP \(\bigcap\) coNP having zero-knowledge arguments is closed under complement. Furthermore, we show that a problem in NP has a statistical zero-knowledge argument \(\)system if and only if its complement has a computational zero-knowledge proof system. What is novel about these results is that they are unconditional, i.e., do not rely on unproven complexity assumptions such as the existence of one-way functions.

Our characterization of zero-knowledge arguments also enables us to prove a variety of other unconditional results about the class of problems in NP having zero-knowledge arguments, such as equivalences between honest-verifier and malicious-verifier zero knowledge, private coins and public coins, inefficient provers and efficient provers, and non-black-box simulation and black-box simulation. Previously, such results were only known unconditionally for zero-knowledge proof systems, or under the assumption that one-way functions exist for zero-knowledge argument systems.

Ron, Dana, Amir Rosenfeld, and Salil Vadhan. “The hardness of the expected decision depth problem.” Information Processing Letters 101, no. 3 (2007): 112-118. Publisher's VersionAbstract

Given a function \(f\) over \(n\) binary variables, and an ordering of the \(n\) variables, we consider the Expected Decision Depth problem. Namely, what is the expected number of bits that need to be observed until the value of the function is determined, when bits of the input are observed according to the given order. Our main finding is that this problem is (essentially) #P-complete. Moreover, the hardness holds even when the function f is represented as a decision tree.

Canetti, Ran, Ron Rivest, Madhu Sudan, Luca Trevisan, Salil Vadhan, and Hoeteck Wee. “Amplifying collision-resistance: A complexity-theoretic treatment.” In A. Menezes, editor, Advances in Cryptology (CRYPTO '07), 4622:264-283. Lecture Notes in Computer Science, Springer-Verlag, 2007. Publisher's VersionAbstract

We initiate a complexity-theoretic treatment of hardness amplification for collision-resistant hash functions, namely the transformation of weakly collision-resistant hash functions into strongly collision-resistant ones in the standard model of computation. We measure the level of collision resistance by the maximum probability, over the choice of the key, for which an efficient adversary can find a collision. The goal is to obtain constructions with short output, short keys, small loss in adversarial complexity tolerated, and a good trade-off between compression ratio and computational complexity. We provide an analysis of several simple constructions, and show that many of the parameters achieved by our constructions are almost optimal in some sense.

Micciancio, Daniele, Shien Jin Ong, Amit Sahai, and Salil Vadhan. “Concurrent zero knowledge without complexity assumptions.” In S. Halevi and T. Rabin, eds., Proceedings of the Third Theory of Cryptography Conference (TCC '06), 3876:1-20. New York, NY, USA: Springer Verlag, Lecture Notes in Computer Science, 2006. Publisher's VersionAbstract

Version History. Full version available at (Attached as ECCC2005).

We provide unconditional constructions of concurrent statistical zero-knowledge proofs for a variety of non-trivial problems (not known to have probabilistic polynomial-time algorithms). The problems include Graph Isomorphism, Graph Nonisomorphism, Quadratic Residuosity, Quadratic Nonresiduosity, a restricted version of Statistical Difference, and approximate versions of the (\(\mathsf{coNP}\) forms of the) Shortest Vector Problem and Closest Vector Problem in lattices. For some of the problems, such as Graph Isomorphism and Quadratic Residuosity, the proof systems have provers that can be implemented in polynomial time (given an \(\mathsf{NP}\) witness) and have \(\tilde{O}(\log n)\) rounds, which is known to be essentially optimal for black-box simulation. To the best of our knowledge, these are the first constructions of concurrent zero-knowledge proofs in the plain, asynchronous model (i.e., without setup or timing assumptions) that do not require complexity assumptions (such as the existence of one-way functions).

Nguyen, Minh-Huyen, Shien Jin Ong, and Salil Vadhan. “Statistical zero-knowledge arguments for NP from any one-way function.” In Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS ‘06), 3-13. IEEE, 2006. Publisher's VersionAbstract

Version History: Merged with STOC '07 paper of Haitner and Reingold. Also available as a journal version. Full version invited to SIAM J. Computing Special Issue on FOCS ‘06

We show that every language in NP has a statistical zero-knowledge argument system under the (minimal) complexity assumption that one-way functions exist. In such protocols, even a computationally unbounded verifier cannot learn anything other than the fact that the assertion being proven is true, whereas a polynomial-time prover cannot convince the verifier to accept a false assertion except with negligible probability. This resolves an open question posed by Naor et al. (1998). Departing from previous works on this problem, we do not construct standard statistically hiding commitments from any one-way function. Instead, we construct a relaxed variant of commitment schemes called "1-out-of-2-binding commitments," recently introduced by Nguyen et al. (2006)

Sahai, Amit, and Salil Vadhan. “A complete problem for statistical zero knowledge.Journal of the ACM 50, no. 2 (2003): 196-249.Abstract
We present the first complete problem for SZK, the class of (promise) problems possessing statistical zero-knowledge proofs (against an honest verifier). The problem, called STATISTICAL DIFFERENCE, is to decide whether two efficiently samplable distributions are either statistically close or far apart. This gives a new characterization of SZK that makes no reference to interaction or zero knowledge.


We propose the use of complete problems to unify and extend the study of statistical zero knowledge. To this end, we examine several consequences of our Completeness Theorem and its proof, such as:

  • A way to make every (honest-verifier) statistical zero-knowledge proof very communication efficient, with the prover sending only one bit to the verifier (to achieve soundness error 1/2).
  • Simpler proofs of many of the previously known results about statistical zero knowledge, such as the Fortnow and Aiello--Håstad upper bounds on the complexity of SZK and Okamoto's result that SZK is closed under complement.
  • Strong closure properties of SZK which amount to constructing statistical zero-knowledge proofs for complex assertions built out of simpler assertions already shown to be in SZK.
  • New results about the various measures of "knowledge complexity," including a collapse in the hierarchy corresponding to knowledge complexity in the "hint" sense.
  • Algorithms for manipulating the statistical difference between efficiently samplable distributions, including transformations which "polarize" and "reverse" the statistical relationship between a pair of distributions.
Vadhan, Salil. “The complexity of counting in sparse, regular, and planar graphs.SIAM Journal on Computing 31, no. 2 (2001): 398-427.Abstract
We show that a number of graph-theoretic counting problems remain NP-hard, indeed #P-complete, in very restricted classes of graphs. In particular, we prove that the problems of counting matchings, vertex covers, independent sets, and extremal variants of these all remain hard when restricted to planar bipartite graphs of bounded degree or regular graphs of constant degree. We obtain corollaries about counting cliques in restricted classes of graphs and counting satisfying assignments to restricted classes of monotone 2-CNF formulae. To achieve these results, a new interpolation-based reduction technique which preserves properties such as constant degree is introduced.
Sahai, Amit, and Salil Vadhan. “ Manipulating statistical difference.Randomization Methods in Algorithm Design (DIMACS Workshop, December 1997), volume 43 of DIMACS Series in Discrete Mathematics and Theoretical Computer Science 43 (1999): 251-270.Abstract

We give several efficient transformations for manipulating the statistical difference (variation distance) between a pair of probability distributions. The effects achieved include increasing the statistical difference, decreasing the statistical difference, "polarizing" the statistical relationship, and "reversing" the statistical relationship. We also show that a boolean formula whose atoms are statements about statistical difference can be transformed into a single statement about statistical difference. All of these transformations can be performed in polynomial time, in the sense that, given circuits which sample from the input distributions, it only takes polynomial time to compute circuits which sample from the output distributions.


By our prior work (see FOCS 97), such transformations for manipulating statistical difference are closely connected to results about SZK, the class of languages possessing statistical zero-knowledge proofs. In particular, some of the transformations given in this paper are equivalent to the closure of SZK under complement and under certain types of Turing reductions. This connection is also discussed briefly in this paper.

Goldreich, Oded, Amit Sahai, and Salil Vadhan. “Honest-verifier statistical zero-knowledge equals general statistical zero-knowledge.Proceedings of the 30th Annual ACM Symposium on Theory of Computing (STOC ‘98) (1998): 399-408.Abstract
We show how to transform any interactive proof system which is statistical zero-knowledge with respect to the honest-verifier, into a proof system which is statistical zero-knowledge with respect to any verifier. This is done by limiting the behavior of potentially cheating verifiers, without using computational assumptions or even referring to the complexity of such verifier strategies. (Previous transformations have either relied on computational assumptions or were applicable only to constant-round public-coin proof systems.)

Our transformation also applies to public-coin (aka Arthur-Merlin) computational zero-knowledge proofs: We transform any Arthur-Merlin proof system which is computational zero-knowledge with respect to the honest-verifier, into an Arthur-Merlin proof system which is computational zero-knowledge with respect to any probabilistic polynomial-time verifier.

A crucial ingredient in our analysis is a new lemma regarding 2-universal hashing functions.