Optimizing Authenticated Garbling for Faster Secure Two-Party Computation

Wang et al. (CCS 2017) recently proposed a protocol for malicious secure two-party computation that represents the state-of-the- art with regard to concrete efficiency in both the single-execution and amortized settings, with or without preprocessing. We show here several optimizations of their protocol that result in a significant improvement in the overall communication and running time. Specifically: - We show how to make the “authenticated garbling” at the heart of their protocol compatible with the half-gate optimization of Zahur et al. (Eurocrypt 2015). We also show how to avoid sending an information-theoretic MAC for each garbled row. These two optimizations give up to a 2.6x improvement in communication, and make the communication of the online phase essentially equivalent to that of state-of-the-art semi-honest secure computation. - We show various optimizations to their protocol for generating AND triples that, overall, result in a 1.5x improvement in the communication and a 2x improvement in the computation for that step

Raziel: Private and Verifiable Smart Contracts on Blockchains

Raziel combines secure multi-party computation and proof-carrying code to provide privacy, correctness and verifiability guarantees for smart contracts on blockchains. Effectively solving DAO and Gyges attacks, this paper describes an implementation and presents examples to demonstrate its practical viability (e.g., private and verifiable crowdfundings and investment funds). Additionally, we show how to use Zero-Knowledge Proofs of Proofs (i.e., Proof-Carrying Code certificates) to prove the validity of smart contracts to third parties before their execution without revealing anything else. Finally, we show how miners could get rewarded for generating pre-processing data for secure multi-party computation.Comment: Support: cothority/ByzCoin/OmniLedge

More Efficient MPC from Improved Triple Generation and Authenticated Garbling

Recent works on distributed garbling have provided highly efficient solutions for constant-round MPC tolerating an arbitrary number of corruptions. In this work, we improve upon state-of-the-art protocols in this paradigm for further performance gain. First, we propose a new protocol for generating authenticated AND triples, which is a key building block in many recent works. -- We propose a new authenticated bit protocol in the two-party and multi-party settings from bare IKNP OT extension, allowing us to reduce the communication by about 24% and eliminate many computation bottlenecks. We further improve the computational efficiency for multi-party authenticated AND triples with cheaper and fewer consistency checks and fewer hash function calls. -- We implemented our triple generation protocol and observe around 4x to 5x improvement compared to the best prior protocol in most settings. For example, in the two-party setting with 10 Gbps network and 8 threads, our protocol can generate more than 4 million authenticated triples per second, while the best prior implementation can only generate 0.8 million triples per second. In the multi-party setting, our protocol can generate more than 37000 triples per second over 80 parties, while the best prior protocol can only generate the same number of triples per second over 16 parties. We also improve the state-of-the-art multi-party authenticated garbling protocol. -- We take the first step towards applying half-gates in the multi-party setting, which enables us to reduce the size of garbled tables by 2\kappa bits per gate per garbler, where \kappa is the computational security parameter. This optimization is also applicable in the semi-honest multi-party setting. -- We further reduce the communication of circuit authentication from 4\rho bits to 1 bit per gate, using a new multi-party batched circuit authentication, where \rho is the statistical security parameter. Prior solution with similar efficiency is only applicable in the two-party setting. For example, in the three-party setting, our techniques can lead to roughly a 35% reduction in the size of a distributed garbled circuit

Fast Evaluation of S-boxes with Garbled Circuits

Garbling schemes are vital primitives for privacy-preserving protocols and for secure two-party computation. This paper presents a projective garbling scheme that assigns $2^n$ values to wires in a circuit comprising XOR and unary projection gates. A generalization of FreeXOR allows the XOR of wires with $2^n$ values to be very efficient. We then analyze the performance of our scheme by evaluating substitution-permutation ciphers. Using our proposal, we measure high-speed evaluation of the ciphers with a moderately increased cost in garbling and bandwidth. Theoretical analysis suggests that for evaluating the nine examined ciphers, one can expect a 4- to 70-fold improvement in evaluation performance with, at most, a 4-fold increase in garbling cost and, at most, an 8-fold increase in communication cost compared to state-of-the-art garbling schemes. In an offline/online setting, such as secure function evaluation as a service, the circuit garbling and communication to the evaluator can proceed before the input phase. Thus our scheme offers a fast online phase. Furthermore, we present efficient computation formulas for the S-boxes of TWINE and Midori64 in Boolean circuits. To our knowledge, our formulas give the smallest number of AND gates for the S-boxes of these two ciphers

Efficient Maliciously Secure Multiparty Computation for RAM

A crucial issue, that mostly affects the performance of actively secure computation of RAM programs, is the task of reading/writing from/to memory in a private and authenticated manner. Previous works in the active security and multiparty settings are based purely on the SPDZ (reactive) protocol, hence, memory accesses are treated just like any input to the computation. However, a garbled-circuit-based construction (such as BMR), which benefits from a lower round complexity, must resolve the issue of converting memory data bits to their corresponding wire keys and vice versa. In this work we propose three techniques to construct a secure memory access, each appropriates to a different level of abstraction of the underlying garbling functionality. We provide a comparison between the techniques by several metrics. To the best of our knowledge, we are the first to construct, prove and implement a concretely efficient garbled-circuit-based actively secure RAM computation with dishonest majority. Our construction is based on our third (most efficient) technique, cleverly utilizing the underlying SPDZ authenticated shares (Damgård et al., Crypto 2012), yields lean circuits and a constant number of communication rounds per physical memory access. Specifically, it requires no additional circuitry on top of the ORAM\u27s, incurs only two rounds of broadcasts between every two memory accesses and has a multiplicative overhead of 2 on top of the ORAM\u27s storage size. Our protocol outperforms the state of the art in this settings when deployed over WAN. Even when simulating a very conservative RTT of 100ms our protocol is at least one order of magnitude faster than the current state of the art protocol of Keller and Scholl (Asiacrypt 2015)

Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications

We present Chameleon, a novel hybrid (mixed-protocol) framework for secure function evaluation (SFE) which enables two parties to jointly compute a function without disclosing their private inputs. Chameleon combines the best aspects of generic SFE protocols with the ones that are based upon additive secret sharing. In particular, the framework performs linear operations in the ring $\mathbb{Z}_{2^l}$ using additively secret shared values and nonlinear operations using Yao's Garbled Circuits or the Goldreich-Micali-Wigderson protocol. Chameleon departs from the common assumption of additive or linear secret sharing models where three or more parties need to communicate in the online phase: the framework allows two parties with private inputs to communicate in the online phase under the assumption of a third node generating correlated randomness in an offline phase. Almost all of the heavy cryptographic operations are precomputed in an offline phase which substantially reduces the communication overhead. Chameleon is both scalable and significantly more efficient than the ABY framework (NDSS'15) it is based on. Our framework supports signed fixed-point numbers. In particular, Chameleon's vector dot product of signed fixed-point numbers improves the efficiency of mining and classification of encrypted data for algorithms based upon heavy matrix multiplications. Our evaluation of Chameleon on a 5 layer convolutional deep neural network shows 133x and 4.2x faster executions than Microsoft CryptoNets (ICML'16) and MiniONN (CCS'17), respectively