Showing papers in "IACR Cryptology ePrint Archive in 2017"

Practical Secure Aggregation for Privacy Preserving Machine Learning.

Abstract: We design a novel, communication-efficient, failure-robust protocol for secure aggregation of high-dimensional data. Our protocol allows a server to compute the sum of large, user-held data vectors from mobile devices in a secure manner (i.e. without learning each user's individual contribution), and can be used, for example, in a federated learning setting, to aggregate user-provided model updates for a deep neural network. We prove the security of our protocol in the honest-but-curious and active adversary settings, and show that security is maintained even if an arbitrarily chosen subset of users drop out at any time. We evaluate the efficiency of our protocol and show, by complexity analysis and a concrete implementation, that its runtime and communication overhead remain low even on large data sets and client pools. For 16-bit input values, our protocol offers $1.73 x communication expansion for 210 users and 220-dimensional vectors, and 1.98 x expansion for 214 users and 224-dimensional vectors over sending data in the clear.

SecureML: A System for Scalable Privacy-Preserving Machine Learning.

Abstract: Machine learning is widely used in practice to produce predictive models for applications such as image processing, speech and text recognition. These models are more accurate when trained on large amount of data collected from different sources. However, the massive data collection raises privacy concerns. In this paper, we present new and efficient protocols for privacy preserving machine learning for linear regression, logistic regression and neural network training using the stochastic gradient descent method. Our protocols fall in the two-server model where data owners distribute their private data among two non-colluding servers who train various models on the joint data using secure two-party computation (2PC). We develop new techniques to support secure arithmetic operations on shared decimal numbers, and propose MPC-friendly alternatives to non-linear functions such as sigmoid and softmax that are superior to prior work. We implement our system in C++. Our experiments validate that our protocols are several orders of magnitude faster than the state of the art implementations for privacy preserving linear and logistic regressions, and scale to millions of data samples with thousands of features. We also implement the first privacy preserving system for training neural networks.

Algorand: Scaling Byzantine Agreements for Cryptocurrencies.

Abstract: Algorand is a new cryptocurrency that confirms transactions with latency on the order of a minute while scaling to many users. Algorand ensures that users never have divergent views of confirmed transactions, even if some of the users are malicious and the network is temporarily partitioned. In contrast, existing cryptocurrencies allow for temporary forks and therefore require a long time, on the order of an hour, to confirm transactions with high confidence. Algorand uses a new Byzantine Agreement (BA) protocol to reach consensus among users on the next set of transactions. To scale the consensus to many users, Algorand uses a novel mechanism based on Verifiable Random Functions that allows users to privately check whether they are selected to participate in the BA to agree on the next set of transactions, and to include a proof of their selection in their network messages. In Algorand's BA protocol, users do not keep any private state except for their private keys, which allows Algorand to replace participants immediately after they send a message. This mitigates targeted attacks on chosen participants after their identity is revealed. We implement Algorand and evaluate its performance on 1,000 EC2 virtual machines, simulating up to 500,000 users. Experimental results show that Algorand confirms transactions in under a minute, achieves 125x Bitcoin's throughput, and incurs almost no penalty for scaling to more users.

Privacy-Preserving Deep Learning via Additively Homomorphic Encryption.

Abstract: We present a privacy-preserving deep learning system in which many learning participants perform neural network-based deep learning over a combined dataset of all, without revealing the participant...

How to Simulate It – A Tutorial on the Simulation Proof Technique

Abstract: One of the most fundamental notions of cryptography is that of simulation. It stands behind the concepts of semantic security, zero knowledge, and security for multiparty computation. However, writing a simulator and proving security via the use of simulation is a nontrivial task, and one that many newcomers to the field often find difficult. In this tutorial, we provide a guide to how to write simulators and prove security via the simulation paradigm. Although we have tried to make this tutorial as stand-alone as possible, we assume some familiarity with the notions of secure encryption, zero-knowledge, and secure computation.

Privacy-Preserving Classification on Deep Neural Network.

Abstract: Neural Networks (NN) are today increasingly used in Machine Learning where they have become deeper and deeper to accurately model or classify high-level abstractions of data. Their development however also gives rise to important data privacy risks. This observation motives Microsoft researchers to propose a framework, called Cryptonets. The core idea is to combine simplifications of the NN with Fully Homomorphic Encryptions (FHE) techniques to get both confidentiality of the manipulated data and efficiency of the processing. While efficiency and accuracy are demonstrated when the number of non-linear layers is small (eg 2), Cryptonets unfortunately becomes ineffective for deeper NNs which let the problem of privacy preserving matching open in these contexts. This work successfully addresses this problem by combining the original ideas of Cryptonets’ solution with the batch normalization principle introduced at ICML 2015 by Ioffe and Szegedy. We experimentally validate the soundness of our approach with a neural network with 6 non-linear layers. When applied to the MNIST database, it competes the accuracy of the best non-secure versions, thus significantly improving Cryptonets.

CRYSTALS - Kyber: A CCA-secure Module-Lattice-Based KEM

Abstract: Rapid advances in quantum computing, together with the announcement by the National Institute of Standards and Technology (NIST) to define new standards for digital-signature, encryption, and key-establishment protocols, have created significant interest in post-quantum cryptographic schemes. This paper introduces Kyber (part of CRYSTALS - Cryptographic Suite for Algebraic Lattices - a package submitted to NIST post-quantum standardization effort in November 2017), a portfolio of post-quantum cryptographic primitives built around a key-encapsulation mechanism (KEM), based on hardness assumptions over module lattices. Our KEM is most naturally seen as a successor to the NEWHOPE KEM (Usenix 2016). In particular, the key and ciphertext sizes of our new construction are about half the size, the KEM offers CCA instead of only passive security, the security is based on a more general (and flexible) lattice problem, and our optimized implementation results in essentially the same running time as the aforementioned scheme. We first introduce a CPA-secure public-key encryption scheme, apply a variant of the Fujisaki-Okamoto transform to create a CCA-secure KEM, and eventually construct, in a black-box manner, CCA-secure encryption, key exchange, and authenticated-key-exchange schemes. The security of our primitives is based on the hardness of Module-LWE in the classical and quantum random oracle models, and our concrete parameters conservatively target more than 128 bits of post-quantum security.

The first collision for full SHA-1.

Abstract: SHA-1 is a widely used 1995 NIST cryptographic hash function standard that was officially deprecated by NIST in 2011 due to fundamental security weaknesses demonstrated in various analyses and theoretical attacks.

Revive: Rebalancing Off-Blockchain Payment Networks.

Abstract: Scaling the transaction throughput of decentralized blockchain ledgers such as Bitcoin and Ethereum has been an ongoing challenge. Two-party duplex payment channels have been designed and used as building blocks to construct linked payment networks, which allow atomic and trust-free payments between parties without exhausting the resources of the blockchain. Once a payment channel, however, is depleted (e.g., because transactions were mostly unidirectional) the channel would need to be closed and re-funded to allow for new transactions. Users are envisioned to entertain multiple payment channels with different entities, and as such, instead of refunding a channel (which incurs costly on-chain transactions), a user should be able to leverage his existing channels to rebalance a poorly funded channel. To the best of our knowledge, we present the first solution that allows an arbitrary set of users in a payment channel network to securely rebalance their channels, according to the preferences of the channel owners. Except in the case of disputes (similar to conventional payment channels), our solution does not require on-chain transactions and therefore increases the scalability of existing blockchains. In our security analysis, we show that an honest participant cannot lose any of its funds while rebalancing. We finally provide a proof of concept implementation and evaluation for the Ethereum network.

Thunderella: Blockchains with Optimistic Instant Confirmation.

Abstract: State machine replication, or “consensus”, is a central abstraction for distributed systems where a set of nodes seek to agree on an ever-growing, linearly-ordered log. In this paper, we propose a practical new paradigm called Thunderella for achieving state machine replication by combining a fast, asynchronous path with a (slow) synchronous “fall-back” path (which only gets executed if something goes wrong); as a consequence, we get simple state machine replications that essentially are as robust as the best synchronous protocols, yet “optimistically” (if a super majority of the players are honest), the protocol “instantly” confirms transactions.

Removal Attacks on Logic Locking and Camouflaging Techniques.

Abstract: With the adoption of a globalized and distributed IC design flow, IP piracy, reverse engineering, and counterfeiting threats are becoming more prevalent. Logic obfuscation techniques including logic locking and IC camouflaging have been developed to address these emergent challenges. A major challenge for logic locking and camouflaging techniques is to resist Boolean satisfiability (SAT) based attacks that can circumvent state-of-the-art solutions within minutes. Over the past year, multiple SAT attack resilient solutions such as Anti-SAT and AND-tree insertion (ATI) have been presented. In this paper, we perform a security analysis of these countermeasures and show that they leave structural traces behind in their attempts to thwart the SAT attack. We present three attacks, namely “signal probability skew” (SPS) attack, “AppSAT guided removal (AGR) attack, and “sensitization guided SAT” (SGS) attack”, that can break Anti-SAT and ATI, within minutes.

ZeroTrace : Oblivious Memory Primitives from Intel SGX.

Abstract: We are witnessing a confluence between applied cryptography and secure hardware systems in enabling secure cloud computing. On one hand, work in applied cryptography has enabled efficient, oblivious data-structures and memory primitives. On the other, secure hardware and the emergence of Intel SGX has enabled a low-overhead and mass market mechanism for isolated execution. By themselves these technologies have their disadvantages. Oblivious memory primitives carry high performance overheads, especially when run non-interactively. Intel SGX, while more efficient, suffers from numerous softwarebased side-channel attacks, high context switching costs, and bounded memory size. In this work we build a new library of oblivious memory primitives, which we call ZeroTrace. ZeroTrace is designed to carefully combine state-of-the-art oblivious RAM techniques and SGX, while mitigating individual disadvantages of these technologies. To the best of our knowledge, ZeroTrace represents the first oblivious memory primitives running on a real secure hardware platform. ZeroTrace simultaneously enables a dramatic speed-up over pure cryptography and protection from softwarebased side-channel attacks. The core of our design is an efficient and flexible block-level memory controller that provides oblivious execution against any active software adversary, and across asynchronous SGX enclave terminations. Performance-wise, the memory controller can service requests for 4 B blocks in 1.2 ms and 1 KB blocks in 3.4 ms (given a 10 GB dataset). On top of our memory controller, we evaluate Set/Dictionary/List interfaces which can all perform basic operations (e.g., get/put/insert).

The QARMA Block Cipher Family. Almost MDS Matrices Over Rings With Zero Divisors, Nearly Symmetric Even-Mansour Constructions With Non-Involutory Central Rounds, and Search Heuristics for Low-Latency S-Boxes

Abstract: This paper introduces QARMA, a new family of lightweight tweakable block ciphers targeted at applications such as memory encryption, the generation of very short tags for hardware-assisted prevention of software exploitation, and the construction of keyed hash functions. QARMA is inspired by reflection ciphers such as PRINCE, to which it adds a tweaking input, and MANTIS. However, QARMA differs from previous reflector constructions in that it is a three-round Even-Mansour scheme instead of a FX-construction, and its middle permutation is non-involutory and keyed . We introduce and analyse a family of Almost MDS matrices defined over a ring with zero divisors that allows us to encode rotations in its operation while maintaining the minimal latency associated to {0, 1}-matrices. The purpose of all these design choices is to harden the cipher against various classes of attacks. We also describe new S-Box search heuristics aimed at minimising the critical path. QARMA exists in 64- and 128-bit block sizes, where block and tweak size are equal, and keys are twice as long as the blocks. We argue that QARMA provides sufficient security margins within the constraints determined by the mentioned applications, while still achieving best-in-class latency. Implementation results on a state-of-the art manufacturing process are reported. Finally, we propose a technique to extend the length of the tweak by using, for instance, a universal hash function, which can also be used to strengthen the security of QARMA.

Pseudorandomness of Ring-LWE for Any Ring and Modulus.

Abstract: We give a polynomial-time quantum reduction from worst-case (ideal) lattice problems directly to decision (Ring-)LWE. This extends to decision all the worst-case hardness results that were previously known for the search version, for the same or even better parameters and with no algebraic restrictions on the modulus or number field. Indeed, our reduction is the first that works for decision Ring-LWE with any number field and any modulus.

Simple Encrypted Arithmetic Library - SEAL v2.1.

Abstract: Achieving fully homomorphic encryption was a longstanding open problem in cryptography until it was resolved by Gentry in 2009. Soon after, several homomorphic encryption schemes were proposed. The early homomorphic encryption schemes were extremely impractical, but recently new implementations, new data encoding techniques, and a better understanding of the applications have started to change the situation. In this paper we introduce the most recent version (v2.1) of Simple Encrypted Arithmetic Library - SEAL, a homomorphic encryption library developed by Microsoft Research, and describe some of its core functionality.

RingCT 2.0: A Compact Accumulator-Based (Linkable Ring Signature) Protocol for Blockchain Cryptocurrency Monero.

Abstract: In this work, we initially study the necessary properties and security requirements of Ring Confidential Transaction (RingCT) protocol deployed in the popular anonymous cryptocurrency Monero. Firstly, we formalize the syntax of RingCT protocol and present several formal security definitions according to its application in Monero. Based on our observations on the underlying (linkable) ring signature and commitment schemes, we then put forward a new efficient RingCT protocol (RingCT 2.0), which is built upon the well-known Pedersen commitment, accumulator with one-way domain and signature of knowledge (which altogether perform the functions of a linkable ring signature). Besides, we show that it satisfies the security requirements if the underlying building blocks are secure in the random oracle model. In comparison with the original RingCT protocol, our RingCT 2.0 protocol presents a significant space saving, namely, the transaction size is independent of the number of groups of input accounts included in the generalized ring while the original RingCT suffers a linear growth with the number of groups, which would allow each block to process more transactions.

State of the Art in Lightweight Symmetric Cryptography

Abstract: Lightweight cryptography has been one of the “hot topics” in symmetric cryptography in the recent years. A huge number of lightweight algorithms have been published, standardized and/or used in commercial products. In this paper, we discuss the different implementation constraints that a “lightweight” algorithm is usually designed to satisfy in both the software and the hardware case. We also present an extensive survey of all lightweight symmetric primitives we are aware of. It covers designs from the academic community, from government agencies and proprietary algorithms which were reverse-engineered or leaked. Relevant national (NIST...) and international (ISO/IEC...) standards are listed. We identified several trends in the design of lightweight algorithms, such as the designers’ preference for ARX-based and bitsliced-S-Box-based designs or simpler key schedules. We also discuss more general trade-offs facing the authors of such algorithms and suggest a clearer distinction between two subsets of lightweight cryptography. The first, ultra-lightweight cryptography, deals with primitives fulfilling a unique purpose while satisfying specific and narrow constraints. The second is ubiquitous cryptography and it encompasses more versatile algorithms both in terms of functionality and in terms of implementation trade-offs.

Threshold Cryptosystems From Threshold Fully Homomorphic Encryption.

Abstract: We develop a general approach to adding a threshold functionality to a large class of (non-threshold) cryptographic schemes. A threshold functionality enables a secret key to be split into a number of shares, so that only a threshold of parties can use the key, without reconstructing the key. We begin by constructing a threshold fully-homomorphic encryption scheme (ThFHE) from the learning with errors (LWE) problem. We next introduce a new concept, called a universal thresholdizer, from which many threshold systems are possible. We show how to construct a universal thresholdizer from our ThFHE. A universal thresholdizer can be used to add threshold functionality to many systems, such as CCA-secure public-key encryption (PKE), signature schemes, pseudorandom functions, and others primitives. In particular, by applying this paradigm to a (non-threshold) lattice signature system, we obtain the first single-round threshold signature scheme from LWE.

Concurrency and Privacy with Payment-Channel Networks.

Abstract: Permissionless blockchains protocols such as Bitcoin are inherently limited in transaction throughput and latency. Current efforts to address this key issue focus on off-chain payment channels that can be combined in a Payment-Channel Network (PCN) to enable an unlimited number of payments without requiring to access the blockchain other than to register the initial and final capacity of each channel. While this approach paves the way for low latency and high throughput of payments, its deployment in practice raises several privacy concerns as well as technical challenges related to the inherently concurrent nature of payments that have not been sufficiently studied so far. In this work, we lay the foundations for privacy and concurrency in PCNs, presenting a formal definition in the Universal Composability framework as well as practical and provably secure solutions. In particular, we present Fulgor and Rayo. Fulgor is the first payment protocol for PCNs that provides provable privacy guarantees for PCNs and is fully compatible with the Bitcoin scripting system. However, Fulgor is a blocking protocol and therefore prone to deadlocks of concurrent payments as in currently available PCNs. Instead, Rayo is the first protocol for PCNs that enforces non-blocking progress (i.e., at least one of the concurrent payments terminates). We show through a new impossibility result that non-blocking progress necessarily comes at the cost of weaker privacy. At the core of Fulgor and Rayo is Multi-Hop HTLC, a new smart contract, compatible with the Bitcoin scripting system, that provides conditional payments while reducing running time and communication overhead with respect to previous approaches. Our performance evaluation of Fulgor and Rayo shows that a payment with 10 intermediate users takes as few as 5 seconds, thereby demonstrating their feasibility to be deployed in practice.

Tesseract: Real-Time Cryptocurrency Exchange using Trusted Hardware.

Abstract: We propose Tesseract, a secure real-time cryptocurrency exchange service. Existing centralized exchange designs are vulnerable to theft of funds, while decentralized exchanges cannot offer real-time cross-chain trades. All currently deployed exchanges are also vulnerable to frontrunning attacks. Tesseract overcomes these flaws and achieves a best-of-both-worlds design by using a trusted execution environment. The task of committing the recent trade data to independent cryptocurrency systems presents an all-or-nothing fairness problem, to which we present ideal theoretical solutions, as well as practical solutions. Tesseract supports not only real-time cross-chain cryptocurrency trades, but also secure tokenization of assets pegged to cryptocurrencies. For instance, Tesseract-tokenized bitcoins can circulate on the Ethereum blockchain for use in smart contracts. We provide a demo implementation of Tesseract that supports Bitcoin, Ethereum, and similar cryptocurrencies.

Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications.

Abstract: 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 $\mathbbZ _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.

Scalable Multi-party Computation for zk-SNARK Parameters in the Random Beacon Model.

Abstract: We present MMORPG, a built system for zero-knowledge succinct non-interactive arguments of knowledge zk-SNARK parameter generation. zk-SNARKs are compact, e cient, and publicly veri able zero-knowedge proofs for arbitrary computation. They have emerged as a valuable tool for veri able computation, privacy preserving protocols, and blockchains. Currently practical schemes require a common reference string (CRS) to be constructed in a one-time setup for each statement. Corruption of this process leads to forged proofs and for applications such as cryptocurrencies, potentially billions of dollars in theft. Ben-Sasson, Chiesa, Green, Tromer and Virza [9] devised a multi-party protocol to securely compute such a CRS, and an adaptation of this protocol was used to construct the CRS for the Zcash cryptocurrency [16]. The trustworthiness of these protocols is obstructed by the need for a precommitment phase which forces the selection of a very small number of participants in advance and requires them to secure their secret randomness throughout the duration of the protocol. Our primary contribution is a more scalable multi-party computation (MPC) protocol, secure in the random beacon model, which omits the precommitment phase. We show that security holds even if an adversary has limited in uence on the beacon. Next, we apply our main result to obtain a two-phase protocol for computing an extended version of the CRS of Groth's zk-SNARK [27]. We show that knowledge soundness is maintained in the generic group model when using this CRS. Finally, we implement and evaluate our system.

Double DIP: Re-Evaluating Security of Logic Encryption Algorithms.

Abstract: Logic encryption is a hardware security technique that uses extra key inputs to lock a given combinational circuit. A recent study by Subramanyan et al. shows that all existing logic encryption techniques can be successfully attacked. As a countermeasure, SARLock was proposed to enhance the security of existing logic encryptions. In this paper, we re-evaluate the security of these approaches. A SAT-based attack called Double DIP is proposed and shown to successfully defeat SARLock-enhanced encryptions.

A Concrete Treatment of Fiat-Shamir Signatures in the Quantum Random-Oracle Model.

Abstract: The Fiat-Shamir transform is a technique for combining a hash function and an identification scheme to produce a digital signature scheme. The resulting scheme is known to be secure in the random oracle model (ROM), which does not, however, imply security in the scenario where the adversary also has quantum access to the oracle. The goal of this current paper is to create a generic framework for constructing tight reductions in the QROM from underlying hard problems to Fiat-Shamir signatures.

Overdrive: Making SPDZ Great Again.

Abstract: SPDZ denotes a multiparty computation scheme in the preprocessing model based on somewhat homomorphic encryption (SHE) in the form of BGV. At CCS ’16, Keller et al. presented MASCOT, a replacement of the preprocessing phase using oblivious transfer instead of SHE, improving by two orders of magnitude on the SPDZ implementation by Damgard et al. (ESORICS ’13). In this work, we show that using SHE is faster than MASCOT in many aspects: 1. We present a protocol that uses semi-homomorphic (addition-only) encryption. For two parties, our BGV-based implementation is six times faster than MASCOT on a LAN and 20 times faster in a WAN setting. The latter is roughly the reduction in communication. 2. We show that using the proof of knowledge in the original work by Damgard et al. (Crypto ’12) is more efficient in practice than the one used in the implementation mentioned above by about one order of magnitude. 3. We present an improvement to the verification of the aforementioned proof of knowledge that increases the performance with a growing number of parties, doubling it for 16 parties.

Forward and Backward Private Searchable Encryption from Constrained Cryptographic Primitives.

Abstract: Using dynamic Searchable Symmetric Encryption, a user with limited storage resources can securely outsource a database to an untrusted server, in such a way that the database can still be searched and updated efficiently. For these schemes, it would be desirable that updates do not reveal any information a priori about the modifications they carry out, and that deleted results remain inaccessible to the server a posteriori. If the first property, called forward privacy, has been the main motivation of recent works, the second one, backward privacy, has been overlooked. In this paper, we study for the first time the notion of backward privacy for searchable encryption. After giving formal definitions for different flavors of backward privacy, we present several schemes achieving both forward and backward privacy, with various efficiency trade-offs. Our constructions crucially rely on primitives such as constrained pseudo-random functions and puncturable encryption schemes. Using these advanced cryptographic primitives allows for a fine-grained control of the power of the adversary, preventing her from evaluating functions on selected inputs, or decrypting specific ciphertexts. In turn, this high degree of control allows our SSE constructions to achieve the stronger forms of privacy outlined above. As an example, we present a framework to construct forward-private schemes from range-constrained pseudo-random functions. Finally, we provide experimental results for implementations of our schemes, and study their practical efficiency.

Fast Private Set Intersection from Homomorphic Encryption.

Abstract: Private Set Intersection (PSI) is a cryptographic technique that allows two parties to compute the intersection of their sets without revealing anything except the intersection. We use fully homomorphic encryption to construct a fast PSI protocol with a small communication overhead that works particularly well when one of the two sets is much smaller than the other, and is secure against semi-honest adversaries. The most computationally efficient PSI protocols have been constructed using tools such as hash functions and oblivious transfer, but a potential limitation with these approaches is the communication complexity, which scales linearly with the size of the larger set. This is of particular concern when performing PSI between a constrained device (cellphone) holding a small set, and a large service provider (e.g. WhatsApp), such as in the Private Contact Discovery application. Our protocol has communication complexity linear in the size of the smaller set, and logarithmic in the larger set. More precisely, if the set sizes are Ny Nx, we achieve a communication overhead of O(Ny log Nx). Our running-time-optimized benchmarks show that it takes 36 seconds of online-computation, 71 seconds of non-interactive (receiver-independent) pre-processing, and only 12.5MB of round trip communication to intersect five thousand 32-bit strings with 16 million 32-bit strings. Compared to prior works, this is roughly a 38--115x reduction in communication with minimal difference in computational overhead.

How (not) to Use Welch's T-test in Side-Channel Security Evaluations.

Abstract: The Test Vector Leakage Assessment (TVLA) methodology is a qualitative tool relying on Welch’s T-test to assess the security of cryptographic implementations against side-channel attacks. Despite known limitations (e.g., risks of false negatives and positives), it is sometimes considered as a pass-fail test to determine whether such implementations are “safe” or not (without clear definition of what is “safe”). In this note, we clarify the limited quantitative meaning of this test when used as a standalone tool. For this purpose, we first show that the straightforward application of this approach to assess the security of a masked implementation is not sufficient. More precisely, we show that even in a simple (more precisely, univariate) case study that seems best suited for the TVLA methodology, detection (or lack thereof) with Welch’s T-test can be totally disconnected from the actual security level of an implementation. For this purpose, we put forward the case of a realistic masking scheme that looks very safe from the TVLA point-of-view and is nevertheless easy to break. We then discuss this result in more general terms and argue that this limitation is shared by all “moment-based” security evaluations. We conclude the note positively, by describing how to use moment-based analyses as a useful ingredient of side-channel security evaluations, to determine a “security order”.

On dual lattice attacks against small-secret LWE and parameter choices in HElib and SEAL.

Abstract: We present novel variants of the dual-lattice attack against LWE in the presence of an unusually short secret. These variants are informed by recent progress in BKW-style algorithms for solving LWE. Applying them to parameter sets suggested by the homomorphic encryption libraries HElib and SEAL yields revised security estimates. Our techniques scale the exponent of the dual-lattice attack by a factor of \((2\,L)/(2\,L+1)\) when \(\log q = \varTheta {\left( L \log n\right) }\), when the secret has constant hamming weight \(h\) and where \(L\) is the maximum depth of supported circuits. They also allow to half the dimension of the lattice under consideration at a multiplicative cost of \(2^{h}\) operations. Moreover, our techniques yield revised concrete security estimates. For example, both libraries promise 80 bits of security for LWE instances with \(n=1024\) and \(\log _2 q \approx {47}\), while the techniques described in this work lead to estimated costs of 68 bits (SEAL) and 62 bits (HElib).