One-One Constrained Pseudorandom Functions

We define and study a new cryptographic primitive, named One-One Constrained Pseudorandom Functions. In this model there are two parties, Alice and Bob, that hold a common random string K, where Alice in addition holds a predicate f:[N] ? {0,1} and Bob in addition holds an input x ? [N]. We then let Alice generate a key K_f based on f and K, and let Bob evaluate a value K_x based on x and K. We consider a third party that sees the values (x,f,K_f) and the goal is to allow her to reconstruct K_x whenever f(x)=1, while keeping K_x pseudorandom whenever f(x)=0. This primitive can be viewed as a relaxation of constrained PRFs, such that there is only a single key query and a single evaluation query. We focus on the information-theoretic setting, where the one-one cPRF has perfect correctness and perfect security. Our main results are as follows. 1) A Lower Bound. We show that in the information-theoretic setting, any one-one cPRF for punctured predicates is of exponential complexity (and thus the lower bound meets the upper bound that is given by a trivial construction). This stands in contrast with the well known GGM-based punctured PRF from OWF, which is in particular a one-one cPRF. This also implies a similar lower bound for all NC1. 2) New Constructions. On the positive side, we present efficient information-theoretic constructions of one-one cPRFs for a few other predicate families, such as equality predicates, inner-product predicates, and subset predicates. We also show a generic AND composition lemma that preserves complexity. 3) An Amplification to standard cPRF. We show that all of our one-one cPRF constructions can be amplified to a standard (single-key) cPRF via any key-homomorphic PRF that supports linear computations. More generally, we suggest a new framework that we call the double-key model which allows to construct constrained PRFs via key-homomorphic PRFs. 4) Relation to CDS. We show that one-one constrained PRFs imply conditional disclosure of secrets (CDS) protocols. We believe that this simple model can be used to better understand constrained PRFs and related cryptographic primitives, and that further applications of one-one constrained PRFs and our double-key model will be found in the future, in addition to those we show in this paper

On Improving Communication Complexity in Cryptography

Cryptography grew to be much more than "the study of secret writing". Modern cryptography is concerned with establishing properties such as privacy, integrity and authenticity in protocols for secure communication and computation. This comes at a price: Cryptographic tools usually introduce an overhead, both in terms of communication complexity (that is, number and size of messages transmitted) and computational efficiency (that is, time and memory required). As in many settings communication between the parties involved is the bottleneck, this thesis is concerned with improving communication complexity in cryptographic protocols. One direction towards this goal is scalable cryptography: In many cryptographic schemes currently deployed, the security degrades linearly with the number of instances (e.g. encrypted messages) in the system. As this number can be huge in contexts like cloud computing, the parameters of the scheme have to be chosen considerably larger - and in particular depending on the expected number of instances in the system - to maintain security guarantees. We advance the state-of-the-art regarding scalable cryptography by constructing schemes where the security guarantees are independent of the number of instances. This allows to choose smaller parameters, even when the expected number of instances is immense. - We construct the first scalable encryption scheme with security against active adversaries which has both compact public keys and ciphertexts. In particular, we significantly reduce the size of the public key to only about 3% of the key-size of the previously most efficient scalable encryption scheme. (Gay,Hofheinz, and Kohl, CRYPTO, 2017) - We present a scalable structure-preserving signature scheme which improves both in terms of public-key and signature size compared to the previously best construction to about 40% and 56% of the sizes, respectively. (Gay, Hofheinz, Kohl, and Pan, EUROCRYPT, 2018) Another important area of cryptography is secure multi-party computation, where the goal is to jointly evaluate some function while keeping each party’s input private. In traditional approaches towards secure multi-party computation either the communication complexity scales linearly in the size of the function, or the computational efficiency is poor. To overcome this issue, Boyle, Gilboa, and Ishai (CRYPTO, 2016) introduced the notion of homomorphic secret sharing. Here, inputs are shared between parties such that each party does not learn anything about the input, and such that the parties can locally evaluate functions on the shares. Homomorphic secret sharing implies secure computation where the communication complexity only depends on the size of the inputs, which is typically much smaller than the size of the function. A different approach towards efficient secure computation is to split the protocol into an input-independent preprocessing phase, where long correlated strings are generated, and a very efficient online phase. One example for a useful correlation are authenticated Beaver triples, which allow to perform efficient multiplications in the online phase such that privacy of the inputs is preserved and parties deviating the protocol can be detected. The currently most efficient protocols implementing the preprocessing phase require communication linear in the number of triples to be generated. This results typically in high communication costs, as the online phase requires at least one authenticated Beaver triple per multiplication. We advance the state-of-the art regarding efficient protocols for secure computation with low communication complexity as follows. - We construct the first homomorphic secret sharing scheme for computing arbitrary functions in NC 1 (that is, functions that are computably by circuits with logarithmic depth) which supports message spaces of arbitrary size, has only negligible correctness error, and does not require expensive multiplication on ciphertexts. (Boyle, Kohl, and Scholl, EUROCRYPT, 2019) - We introduce the notion of a pseudorandom correlation generator for general correlations. Pseudorandom correlation generators allow to locally extend short correlated seeds into long pseudorandom correlated strings. We show that pseudorandom correlation generators can replace the preprocessing phase in many protocols, leading to a preprocessing phase with sublinear communication complexity. We show connections to homomorphic secret sharing schemes and give the first instantiation of pseudorandom correlation generators for authenticated Beaver triples at reasonable computational efficiency. (Boyle, Couteau, Gilboa, Ishai, Kohl, and Scholl, CRYPTO, 2019

Ring Learning With Errors: A crossroads between postquantum cryptography, machine learning and number theory

The present survey reports on the state of the art of the different cryptographic functionalities built upon the ring learning with errors problem and its interplay with several classical problems in algebraic number theory. The survey is based to a certain extent on an invited course given by the author at the Basque Center for Applied Mathematics in September 2018.Comment: arXiv admin note: text overlap with arXiv:1508.01375 by other authors/ comment of the author: quotation has been added to Theorem 5.

Hiding secrets in public random functions

Constructing advanced cryptographic applications often requires the ability of privately embedding messages or functions in the code of a program. As an example, consider the task of building a searchable encryption scheme, which allows the users to search over the encrypted data and learn nothing other than the search result. Such a task is achievable if it is possible to embed the secret key of an encryption scheme into the code of a program that performs the "decrypt-then-search" functionality, and guarantee that the code hides everything except its functionality. This thesis studies two cryptographic primitives that facilitate the capability of hiding secrets in the program of random functions. 1. We first study the notion of a private constrained pseudorandom function (PCPRF). A PCPRF allows the PRF master secret key holder to derive a public constrained key that changes the functionality of the original key without revealing the constraint description. Such a notion closely captures the goal of privately embedding functions in the code of a random function. Our main contribution is in constructing single-key secure PCPRFs for NC^1 circuit constraints based on the learning with errors assumption. Single-key secure PCPRFs were known to support a wide range of cryptographic applications, such as private-key deniable encryption and watermarking. In addition, we build reusable garbled circuits from PCPRFs. 2. We then study how to construct cryptographic hash functions that satisfy strong random oracle-like properties. In particular, we focus on the notion of correlation intractability, which requires that given the description of a function, it should be hard to find an input-output pair that satisfies any sparse relations. Correlation intractability captures the security properties required for, e.g., the soundness of the Fiat-Shamir heuristic, where the Fiat-Shamir transformation is a practical method of building signature schemes from interactive proof protocols. However, correlation intractability was shown to be impossible to achieve for certain length parameters, and was widely considered to be unobtainable. Our contribution is in building correlation intractable functions from various cryptographic assumptions. The security analyses of the constructions use the techniques of secretly embedding constraints in the code of random functions

Circuit-ABE from LWE: Unbounded Attributes and Semi-adaptive Security

We construct an LWE-based key-policy attribute-based encryption (ABE) scheme that supports attributes of unbounded polynomial length. Namely, the size of the public parameters is a fixed polynomial in the security parameter and a depth bound, and with these fixed length parameters, one can encrypt attributes of arbitrary length. Similarly, any polynomial size circuit that adheres to the depth bound can be used as the policy circuit regardless of its input length (recall that a depth d circuit can have as many as 2d inputs). This is in contrast to previous LWE-based schemes where the length of the public parameters has to grow linearly with the maximal attribute length. We prove that our scheme is semi-adaptively secure, namely, the adversary can choose the challenge attribute after seeing the public parameters (but before any decryption keys). Previous LWE-based constructions were only able to achieve selective security. (We stress that the “complexity leveraging” technique is not applicable for unbounded attributes). We believe that our techniques are of interest at least as much as our end result. Fundamentally, selective security and bounded attributes are both shortcomings that arise out of the current LWE proof techniques that program the challenge attributes into the public parameters. The LWE toolbox we develop in this work allows us to delay this programming. In a nutshell, the new tools include a way to generate an a-priori unbounded sequence of LWE matrices, and have fine-grained control over which trapdoor is embedded in each and every one of them, all with succinct representation.National Science Foundation (U.S.) (Award CNS-1350619)National Science Foundation (U.S.) (Grant CNS-1413964)United States-Israel Binational Science Foundation (Grant 712307

Reusable garbled gates for new fully homomorphic encryption service

In this paper, we propose a novel way to provide a fully homomorphic encryption service, namely by using garbled circuits. From a high level perspective, garbled circuits and fully homomorphic encryption, both aim at implementing complex computation on ciphertexts. We define a new cryptographic primitive named reusable garbled gate, which comes from the area of garbled circuits, then based on this new primitive we show that it is very easy to construct a fully homomorphic encryption. However, the instantiation of reusable garbled gates is rather difficult, in fact, we can only instantiate this new primitive based on indistinguishable obfuscation. Furthermore, reusable garbled gates can be a core component for constructing the reusable garbled circuits, which can reduce the communication complexity of them from O(n) to O(1). We believe that reusable garbled gates promise a new way to provide fully homomorphic encryption and reusable garbled circuits service fast.Peer ReviewedPostprint (author's final draft

Semi-Trusted Mixer Based Privacy Preserving Distributed Data Mining for Resource Constrained Devices

In this paper a homomorphic privacy preserving association rule mining algorithm is proposed which can be deployed in resource constrained devices (RCD). Privacy preserved exchange of counts of itemsets among distributed mining sites is a vital part in association rule mining process. Existing cryptography based privacy preserving solutions consume lot of computation due to complex mathematical equations involved. Therefore less computation involved privacy solutions are extremely necessary to deploy mining applications in RCD. In this algorithm, a semi-trusted mixer is used to unify the counts of itemsets encrypted by all mining sites without revealing individual values. The proposed algorithm is built on with a well known communication efficient association rule mining algorithm named count distribution (CD). Security proofs along with performance analysis and comparison show the well acceptability and effectiveness of the proposed algorithm. Efficient and straightforward privacy model and satisfactory performance of the protocol promote itself among one of the initiatives in deploying data mining application in RCD.Comment: IEEE Publication format, International Journal of Computer Science and Information Security, IJCSIS, Vol. 8 No. 1, April 2010, USA. ISSN 1947 5500, http://sites.google.com/site/ijcsis

Constrained Pseudorandom Functions from Homomorphic Secret Sharing

We propose and analyze a simple strategy for constructing 1-key constrained pseudorandom functions (CPRFs) from homomorphic secret sharing. In the process, we obtain the following contributions. First, we identify desirable properties for the underlying HSS scheme for our strategy to work. Second, we show that (most) recent existing HSS schemes satisfy these properties, leading to instantiations of CPRFs for various constraints and from various assumptions. Notably, we obtain the first (1-key selectively secure, private) CPRFs for inner-product and (1-key selectively secure) CPRFs for NC 1 from the DCR assumption, and more. Lastly, we revisit two applications of HSS, equipped with these additional properties, to secure computation: we obtain secure computation in the silent preprocessing model with one party being able to precompute its whole preprocessing material before even knowing the other party, and we construct one-sided statistically secure computation with sublinear communication for restricted forms of computation

Privately Constraining and Programming PRFs, the LWE Way

*Constrained* pseudorandom functions allow for delegating ``constrained\u27\u27 secret keys that let one compute the function at certain authorized inputs---as specified by a constraining predicate---while keeping the function value at unauthorized inputs pseudorandom. In the *constraint-hiding* variant, the constrained key hides the predicate. On top of this, *programmable* variants allow the delegator to explicitly set the output values yielded by the delegated key for a particular set of unauthorized inputs. Recent years have seen rapid progress on applications and constructions of these objects for progressively richer constraint classes, resulting most recently in constraint-hiding constrained PRFs for arbitrary polynomial-time constraints from Learning With Errors~(LWE) [Brakerski, Tsabary, Vaikuntanathan, and Wee, TCC\u2717], and privately programmable PRFs from indistinguishability obfuscation (iO) [Boneh, Lewi, and Wu, PKC\u2717]. In this work we give a unified approach for constructing both of the above kinds of PRFs from LWE with subexponential $\exp(n^{\varepsilon})$ approximation factors. Our constructions follow straightforwardly from a new notion we call a *shift-hiding shiftable function*, which allows for deriving a key for the sum of the original function and any desired hidden shift function. In particular, we obtain the first privately programmable PRFs from non-iO assumptions