The area of "computing with encrypted data" has been studied by numerous authors in the past twenty years since it is fundamental to understanding properties of encryption and it has many practical applications. The related fundamental area of "secure function evaluation" has been studied since the mid 80's. In its basic two-party case, two parties (Alice and Bob) evaluate a known circuit over private inputs (or a private input and a private circuit). Much attention has been paid to the important issue of minimizing rounds of computation in this model. Namely, the number of communication rounds in which Alice and Bob need to engage in to evaluate a circuit on encrypted data securely. Advancements in these areas have been recognized as open problems and have remained open for a number of years. In this paper we give a one round, and thus round optimal, protocol for secure evaluation of circuits which is in polynomial time for NC/sup 1/ circuits. The protocol involves an input party sending encrypted input to a second party, a cryptocomputer, which evaluates the circuit (or a known circuit over its additional private input) non-interactively, securely and obliviously, and provides the output to the input party without learning it. This improves on previous (general) results that are specialized to the case of NC/sup 1/ circuits and require a constant number of communication rounds. We further suggest applications to network and mobile computing.
The area of "computing with encrypted data" has been studied by numerous authors in the past twenty years since it is fundamental to understanding properties of encryption and it has many practical applications. The related fundamental area of "secure function evaluation" has been studied since the mid 80's. In its basic two-party case, two parties (Alice and Bob) evaluate a known circuit over private inputs (or a private input and a private circuit). Much attention has been paid to the important issue of minimizing rounds of computation in this model. Namely, the number of communication rounds in which Alice and Bob need to engage in to evaluate a circuit on encrypted data securely. Advancements in these areas have been recognized as open problems and have remained open for a number of years. In this paper we give a one round, and thus round optimal, protocol for secure evaluation of circuits which is in polynomial time for NC/sup 1/ circuits. The protocol involves an input party sending encrypted input to a second party, a cryptocomputer, which evaluates the circuit (or a known circuit over its additional private input) non-interactively, securely and obliviously, and provides the output to the input party without learning it. This improves on previous (general) results that are specialized to the case of NC/sup 1/ circuits and require a constant number of communication rounds. We further suggest applications to network and mobile computing.
We consider the problem of private function evaluation (PFE) in the two-party setting. Here, informally, one party holds an input x while the other holds a circuit describing a function f; the goal is for one (or both) of the parties to learn f(x) while revealing nothing more to either party. In contrast to the usual setting of secure computation — where the function being computed is known to both parties — PFE is useful in settings where the function (i.e., algorithm) itself must remain secret, e.g., because it is proprietary or classified. It is known that PFE can be reduced to standard secure computation by having the parties evaluate a universal circuit, and this is the approach taken in most prior work. Using a universal circuit, however, introduces additional overhead and results in a more complex implementation. We show here a completely new technique for PFE that avoids universal circuits, and results in constant-round protocols with communication/computational complexity linear in the size of the circuit computing f. This gives the first constant-round protocol for PFE with linear complexity (without using fully homomorphic encryption), even restricted to semi-honest adversaries. 1
In this dissertation, we address several issues that arise in protecting communication between parties, as well as in the area of secure function evaluation. Intuitively, the notion of secure function evaluation is clear and natural: several parties wish to compute some function of their inputs without revealing any information about the inputs, other than what is implied by the value of the function. Research included in this dissertation follows three main directions, briefly described below. The first direction (Chapters 3 and 4) is the design of efficient protocols for concrete functions of interest. Specifically, we present new, more efficient protocols for securely computing the Greater Than (GT) function on the inputs of two parties. Secure evaluation of GT is frequently needed in financial transactions. We introduce new primitives, which are convenient building blocks for more complex tasks, and generalize our GT solutions to satisfy them. Based on this, we construct secure auction protocols, protocols for determining whether an integer lies on an interval, and others. The second direction (Chapter 5) is a fundamental approach to secure evaluation of any function, given as a boolean circuit. We present a very efficient information-theoretic (IT) reduction from the problem of secure evaluation of a polysize formula (or, equivalently, a log-depth boolean circuit) to Oblivious Transfer (a fundamental well-researched cryptographic primitive). Our cost of evaluating each gate of the formula is quadratic in its depth, while in previous reductions it was exponential. Our constructions imply efficient one-round protocols for evaluation of polysize formulas on the players' inputs. We extend our solutions to evaluation of polysize circuits, at the cost of having only computational security. The third direction (Chapter 6) is research on key exchange (KE). In contrast with the previous two directions, here the goal is for two parties to protect their communication against eavesdropping and active interference of an external attacker. KE is a basic procedure, frequently used to establish secure channels between parties. It is a prerequisite to a large number of protocols, including those of the above two directions. We demonstrate a subtle flaw in a previous family of KE protocols and give new KE definitions for the following practical "bank" setting. Here, a server wishes to exchange a key with a client. They have a shared password, and the client carries a "bank card", capable of storing several cryptographic keys. Finally, we present new, more efficient KE protocols for this setting, and prove their security.
Yao's classical millionaires' problem is about securely determining whether x>y, given two input values x, y, which are held as private inputs by two parties, respectively. The output which is result of comparison becomes known to both parties. In this paper we consider a variant of comparison problem in which the inputs x, y are encrypted and the actual values are not known to the parties. Our first solution deals with single comparison; however, in many applications, we encounter situations where it is necessary to make multiple comparisons to find the maximum among several encrypted data, so we make a modification to our first protocol to solve the multiple comparisons problem. Such a secure comparison is an important building block for applications like privacy preserving data mining and secure business. Our second protocol is based on Homomorphic encryption which achieves very low communication and computational complexities. Also our protocols can be performed in constant rounds and do not use general circuit evaluation techniques so they are more efficient than circuit based ones but not general. Implementation is easy and fast.
We consider a minimal scenario for secure computation: Parties A and B have private inputs x and y and a shared random string r. A and B are each allowed to send a single message to a third party C, from which C is to learn the value of f(x, y) for some function f, but nothing else. We show that this model is surprisingly powerful: every function f can be securely computed in this fashion. If the messages are required to be of polynomial size, then we exhibit an efficient protocol for any function f computable in nondeterministic logspace. Using a computational notion of security, we exhibit efficient protocols for any polynomial-time computable function f, assuming the existence of one-way functions. The above results generalize to the case where there are more than two parties with private inputs. The minimalistic nature of our model makes it easy to transform positive results achieved in our model to other more general models of secure computation. It also gives hope for lowerbound proofs. We give an alternative characterization of our model in terms of graph embeddings, and use this to show that for most Boolean functions on {0, 1} n × {0, 1} n, the need to hide just one of the input bits from C requires a communication overhead of n bits. 1
The need for Cryptography arises out of the following fundamental question: can we perform useful computation while ensuring that an adversary does not learn anything about our private sensitive data? The notion of secure multiparty computation (MPC) \\cite{Yao82,GMW87} is a unifying framework for general secure protocols. MPC allows mutually distrusting parties to jointly evaluate any efficiently computable function on their private inputs in such a manner that each party does not learn anything beyond the output of the function. In this thesis, we study the question of building MPC protocols in various security models from standard cryptographic assumptions while minimizing the number of rounds of interaction amongst parties. In the first part of this thesis, (in a joint work with Vipul Goyal, Abhishek Jain, Yael Kalai, Dakshita Khurana and Amit Sahai, CRYPTO 2018) we construct the first round-optimal (i.e., four round) MPC protocol for general functions based on polynomially hard DDH (or QR or Nth-Residuosity) in the plain model where parties have access to no trusted setup. We further show how to overcome the four-round barrier for MPC by constructing a three-round protocol for ``list coin-tossing'' -- a slight relaxation of coin-tossing that suffices for most conceivable applications -- based on polynomially hard DDH (or QR or Nth-Residuosity). This result generalizes to randomized input-less functionalities. Previously, four round MPC protocols required sub-exponential-time hardness assumptions and no multi-party three-round protocols were known for any relaxed security notions with polynomial-time simulation against malicious adversaries. In order to build these protocols, we devise a new {\\em partitioned simulation} technique for MPC where the simulator uses different strategies for simulating the view of aborting adversaries and non-aborting adversaries. The protagonist of this technique is a new notion of {\\em promise zero knowledge} (ZK) where the ZK property only holds against non-aborting verifiers. We show how to realize promise ZK in three rounds in the simultaneous-message model assuming polynomially hard DDH (or QR or Nth-Residuosity). We also rely upon a new {\\em leveled rewinding security} technique that can be viewed as a polynomial-time alternative to leveled complexity leveraging for achieving ``non-malleability'' across different primitives. Then, we also we study the round complexity of concurrently secure multi-party computation (MPC) with super-polynomial simulation (SPS) in the plain model (in a joint work with Vipul Goyal, Abhishek Jain, Dakshita Khurana and Amit Sahai, TCC 2017). In the plain model, there are known explicit attacks that show that concurrently secure MPC with polynomial simulation is impossible to achieve; SPS security is the most widely studied model for concurrently secure MPC in the plain model. We construct a three-round concurrent MPC with SPS security against Byzantine adversaries, assuming sub-exponentially secure DDH and LWE. Prior to our work, the best known round complexity for SPS concurrent MPC was around twenty, although to the best of our knowledge, no previous work even gave an approximation of the constant round complexity that is sufficient for concurrent MPC.In the second part of the thesis, (in a joint work with Abhishek Jain, Rafail Ostrovsky and Ivan Visconti, ASIACRYPT 2018), we study the problem of non-interactive secure computation in the stateless hardware token model where parties have access to physical hardware as part of a trusted setup phase. The notion of non-interactive secure computation (NISC) first introduced in the work of Ishai et al. [EUROCRYPT 2011] studies the following problem: Suppose a receiver R wishes to publish an encryption of her secret input y so that any sender S with input x can then send a message m that reveals f(x,y) to R (for some function f). Here, m can be viewed as an encryption of f(x,y) that can be decrypted by R. NISC requires security against both malicious senders and receivers, and also requires the receiver's message to be reusable across multiple computations (w.r.t. a fixed input of the receiver). All previous solutions to this problem necessarily rely upon OT (or specific number-theoretic assumptions) even in the common reference string model or the random oracle model or to achieve weaker notions of security such as super-polynomial-time simulation. In this work, we construct a NISC protocol based on the minimal assumption of one way functions, in the stateless hardware token model. Our construction achieves UC security and requires a single token sent by the receiver to the sender.
We introduce a new cryptographic primitive called laconic function evaluation (LFE). Using LFE, Alice can compress a large circuit f into a small digest. Bob can encrypt some data x under this digest in a way that enables Alice to recover f(x) without learning anything else about Bob's data. For the scheme to be laconic, we require that the size of the digest, the run-time of the encryption algorithm and the size of the ciphertext should all be small, much smaller than the circuit-size of f. We construct an LFE scheme for general circuits under the learning with errors (LWE) assumption, where the above parameters only grow polynomially with the depth but not the size of the circuit. We then use LFE to construct secure 2-party and multi-party computation (2PC, MPC) protocols with novel properties: We construct a 2-round 2PC protocol between Alice and Bob with respective inputs xA, xBin which Alice learns the output f(xA, xB) in the second round. This is the first such protocol which is “Bob-optimized”, meaning that Alice does all the work while Bob's computation and the total communication of the protocol are smaller than the size of the circuit f or even Alice's input xA. In contrast, prior solutions based on fully homomorphic encryption are “Alice-optimized”. . We construct an MPC protocol, which allows N parties to securely evaluate a function f(x1, ..., xN) over their respective inputs, where the total amount of computation performed by the parties during the protocol execution is smaller than that of evaluating the function itself! Each party has to individually pre-process the circuit f before the protocol starts and post-process the protocol transcript to recover the output after the protocol ends, and the cost of these steps is larger than the circuit size. However, this gives the first MPC where the computation performed by each party during the actual protocol execution, from the time the first protocol message is sent until the last protocol message is received, is smaller than the circuit size.