Some remarks on how to hash faster onto elliptic curves

This article proposes four optimizations of indifferentiable hashing onto (prime-order subgroups of) ordinary elliptic curves over finite fields $\mathbb{F}_{\!q}$. One of them is dedicated to elliptic curves $E$ without non-trivial automorphisms provided that $q \equiv 2 \ (\mathrm{mod} \ 3)$. The second deals with $q \equiv 2, 4 \ (\mathrm{mod} \ 7)$ and an elliptic curve $E_7$ of $j$-invariant $-3^3 5^3$. The corresponding section plays a rather theoretical role, because (the quadratic twist of) $E_7$ is not used in real-world cryptography. The other two optimizations take place for the subgroups $\mathbb{G}_1$, $\mathbb{G}_2$ of pairing-friendly curves. The performance gain comes from the smaller number of required exponentiations in $\mathbb{F}_{\!q}$ for hashing to $E(\mathbb{F}_{\!q})$, $E_7(\mathbb{F}_{\!q})$, and $\mathbb{G}_2$ as well as from the absence of necessity to hash directly onto $\mathbb{G}_1$ in certain settings. In particular, the last insight allows to drastically speed up verification of the aggregate BLS signature incorporated in many blockchain technologies. The new results affect, for example, the pairing-friendly curve BLS12-381 (the most popular in practice at the moment) and a few plain curves from the American standard NIST SP 800-186. Among other things, a taxonomy of state-of-the-art hash functions to elliptic curves is presented. Finally, the article discusses how to hash over highly $2$-adic fields $\mathbb{F}_{\!q}$

Computing 22-isogenies between Kummer lines

We use theta groups to study $2$-isogenies between Kummer lines, with a particular focus on the Montgomery model. This allows us to recover known formula, along with more efficient forms for translated isogenies, which require only $2S+2m_0$ for evaluation. We leverage these translated isogenies to build a hybrid ladder for scalar multiplication on Montgomery curves with rational $2$-torsion which cost $3M+6S+2m_0$ by bits, compared to $5M+4S+1m_0$ for the standard Montgomery ladder

Conditional Attribute-Based Proxy Re-Encryption: Definitions and Constructions from LWE

Attribute-based proxy re-encryption (AB-PRE) is one of the essential variants for proxy re-encryption. It allows a proxy with a re-encryption key to transform a ciphertext associated with an access policy and decryptable by a delegator into another ciphertext associated with a new access policy, thereafter other delegatees can decrypt. However, with AB-PRE, the proxy is to switch the underlying policies of all ciphertexts indiscriminately. The delegator cannot decide which ciphertext would be transformed, taking no flexibility in controlling it for real use. In this paper, we propose a notion of Conditional AB-PRE (CAB-PRE), supporting completely fine-grained control for ciphertexts, in both decryption and delegation. In CAB-PRE, the proxy can convert the underlying policy of a ciphertext only if this ciphertext satisfies a specific condition set by the delegator in the re-encryption key. We formalize the security of this notion in the honest re-encryption attacks (HRA) setting, and present a concrete construction secure under adaptive corruptions in the standard model. As a building block, we design an adaptively HRA-secure (ciphertext-policy) AB-PRE based on the learning with errors (LWE) problem, which solves an open problem left by Susilo et al. in ESORICS \u2721. Finally, we introduce a well-matched conditional delegation tailored to inner-product predicates and integrate it into this AB-PRE to derive our HRA-secure CAB-PRE scheme

Computational Differential Privacy for Encrypted Databases Supporting Linear Queries

Differential privacy is a fundamental concept for protecting individual privacy in databases while enabling data analysis. Conceptually, it is assumed that the adversary has no direct access to the database, and therefore, encryption is not necessary. However, with the emergence of cloud computing and the «on-cloud» storage of vast databases potentially contributed by multiple parties, it is becoming increasingly necessary to consider the possibility of the adversary having (at least partial) access to sensitive databases. A consequence is that, to protect the on-line database, it is now necessary to employ encryption. At PoPETs\u2719, it was the first time that the notion of differential privacy was considered for encrypted databases, but only for a limited type of query, namely histograms. Subsequently, a new type of query, summation, was considered at CODASPY\u2722. These works achieve statistical differential privacy, by still assuming that the adversary has no access to the encrypted database. In this paper, we argue that it is essential to assume that the adversary may eventually access the encrypted data, rendering statistical differential privacy inadequate. Therefore, the appropriate privacy notion for encrypted databases that we use is computational differential privacy, which was introduced by Beimel et al. at CRYPTO \u2708. In our work, we focus on the case of functional encryption, which is an extensively studied primitive permitting some authorized computation over encrypted data. Technically, we show that any randomized functional encryption scheme that satisfies simulation-based security and differential privacy of the output can achieve computational differential privacy for multiple queries to one database. Our work also extends the summation query to a much broader range of queries, specifically linear queries, by utilizing inner-product functional encryption. Hence, we provide an instantiation for inner-product functionalities by proving its simulation soundness and present a concrete randomized inner-product functional encryption with computational differential privacy against multiple queries. In term of efficiency, our protocol is almost as practical as the underlying inner product functional encryption scheme. As evidence, we provide a full benchmark, based on our concrete implementation for databases with up to 1 000 000 entries. Our work can be considered as a step towards achieving privacy-preserving encrypted databases for a wide range of query types and considering the involvement of multiple database owners

On Hilbert-Poincaré series of affine semi-regular polynomial sequences and related Gröbner bases

Gröbner bases are nowadays central tools for solving various problems in commutative algebra and algebraic geometry. A typical use of Gröbner bases is the multivariate polynomial system solving, which enables us to construct algebraic attacks against post-quantum cryptographic protocols. Therefore, the determination of the complexity of computing Gröbner bases is very important both in theory and in practice: One of the most important cases is the case where input polynomials compose an (overdetermined) affine semi-regular sequence. The first part of this paper aims to present a survey on the Gröbner basis computation and its complexity. In the second part, we shall give an explicit formula on the (truncated) Hilbert-Poincaré series associated to the homogenization of an affine semi-regular sequence. Based on the formula, we also study (reduced) Gröbner bases of the ideals generated by an affine semi-regular sequence and its homogenization. Some of our results are considered to give mathematically rigorous proofs of the correctness of methods for computing Gröbner bases of the ideal generated by an affine semi-regular sequence

Tree-based Lookup Table on Batched Encrypted Queries using Homomorphic Encryption

Homomorphic encryption (HE) is in the spotlight as a solution for privacy-related issues in various real-world scenarios. However, the limited types of operations supported by each HE scheme have been a major drawback in applications. While HE schemes based on learning-with-error (LWE) problem provide efficient lookup table (LUT) evaluation in terms of latency, they have downsides in arithmetic operations and low throughput compared to HE schemes based on ring LWE (RLWE) problem. The use of HE on circuits containing LUT has been partly limited if they contain arithmetic operations or their computational width is large. In this paper, we propose homomorphic algorithms for batched queries on LUTs by using RLWE-based HE schemes. To look up encrypted LUTs of size $n$ on encrypted queries, our algorithms use $O(\log{n})$ homomorphic comparisons and $O(n)$ multiplications. For unencrypted LUTs, our algorithms use $O(\log{n})$ comparisons, $O(\sqrt{n})$ ciphertext multiplications, and $O(n)$ scalar multiplications. We provide a proof-of-concept implementation based on CKKS scheme (Asiacrypt 2017). The amortized running time for an encrypted (Resp. unencrypted) LUT of size $512$ is $0.041$ (Resp. $0.025$) seconds. Our implementation reported roughly $2.4$-$6.0$x higher throughput than the current implementation of LWE-based schemes, with more flexibility on the structure of the LUTs

OBSCURE: Versatile Software Obfuscation from a Lightweight Secure Element

Software obfuscation is a powerful tool to protect the intellectual property or secret keys inside programs. Strong software obfuscation is crucial in the context of untrusted execution environments (e.g., subject to malware infection) or to face potentially malicious users trying to reverse-engineer a sensitive program. Unfortunately, the state-of-the-art of pure software-based obfuscation (including white-box cryptography) is either insecure or infeasible in practice. This work introduces OBSCURE, a versatile framework for practical and cryptographically strong software obfuscation relying on a simple stateless secure element (to be embedded, for example, in a protected hardware chip or a token). Based on the foundational result by Goyal et al. from TCC 2010, our scheme enjoys provable security guarantees, and further focuses on practical aspects, such as efficient execution of the obfuscated programs, while maintaining simplicity of the secure element. In particular, we propose a new rectangular universalization technique, which is also of independent interest. We provide an implementation of OBSCURE taking as input a program source code written in a subset of the C programming language. This ensures usability and a broad range of applications of our framework. We benchmark the obfuscation on simple software programs as well as on cryptographic primitives, hence highlighting the possible use cases of the framework as an alternative to pure software-based white-box implementations

Making an Asymmetric PAKE Quantum-Annoying by Hiding Group Elements

The KHAPE-HMQV protocol is a state-of-the-art highly efficient asymmetric password-authenticated key exchange protocol that provides several desirable security properties, but has the drawback of being vulnerable to quantum adversaries due to its reliance on discrete logarithm-based building blocks: solving a single discrete logarithm allows the attacker to perform an offline dictionary attack and recover the password. We show how to modify KHAPE-HMQV to make the protocol quantum-annoying: a classical adversary who has the additional ability to solve discrete logarithms can only break the protocol by solving a discrete logarithm for each guess of the password. While not fully resistant to attacks by quantum computers, a quantum-annoying protocol could offer some resistance to quantum adversaries for whom discrete logarithms are relatively expensive. Our modification to the protocol is small: encryption (using an ideal cipher) is added to one message. Our analysis uses the same ideal cipher model assumption as the original analysis of KHAPE, and quantum annoyingness is modelled using an extension of the generic group model which gives a classical adversary a discrete logarithm oracle

Breaking DPA-protected Kyber via the pair-pointwise multiplication

We introduce a novel template attack for secret key recovery in Kyber, leveraging side-channel information from polynomial multiplication during decapsulation. Conceptually, our attack exploits that Kyber\u27s incomplete number-theoretic transform (NTT) causes each secret coefficient to be used multiple times, unlike when performing a complete NTT. Our attack is a single trace \emph{known} ciphertext attack that avoids machine-learning techniques and instead relies on correlation-matching only. Additionally, our template generation method is very simple and easy to replicate, and we describe different attack strategies, varying on the number of templates required. Moreover, our attack applies to both masked implementations as well as designs with multiplication shuffling. We demonstrate its effectiveness by targeting a masked implementation from the \emph{mkm4} repository. We initially perform simulations in the noisy Hamming-Weight model and achieve high success rates with just $13\,316$ templates while tolerating noise values up to $\sigma=0.3$. In a practical setup, we measure power consumption and notice that our attack falls short of expectations. However, we introduce an extension inspired by known online template attacks, enabling us to recover $128$ coefficient pairs from a single polynomial multiplication. Our results provide evidence that the incomplete NTT, which is used in Kyber-768 and similar schemes, introduces an additional side-channel weakness worth further exploration

Cache Side-Channel Attacks Through Electromagnetic Emanations of DRAM Accesses

Remote side-channel attacks on processors exploit hardware and micro-architectural effects observable from software measurements. So far, the analysis of micro-architectural leakages over physical side-channels (power consumption, electromagnetic field) received little treatment. In this paper, we argue that those attacks are a serious threat, especially against systems such as smartphones and Internet-of-Things (IoT) devices which are physically exposed to the end-user. Namely, we show that the observation of Dynamic Random Access Memory (DRAM) accesses with an electromagnetic (EM) probe constitutes a reliable alternative to time measurements in cache side-channel attacks. We describe the EVICT+EM attack, that allows recovering a full AES key on a T-Tables implementation with similar number of encryptions than state-of-the-art EVICT+RELOAD attacks on the studied ARM platforms. This new attack paradigm removes the need for shared memory and exploits EM radiations instead of high precision timers. Then, we introduce PRIME+EM, which goal is to reverse-engineer cache usage patterns. This attack allows to recover the layout of lookup tables within the cache. Finally, we present COLLISION+EM, a collision-based attack on a System-on-chip (SoC) that does not require malicious code execution, and show its practical efficiency in recovering key material on an ARM TrustZone application. Those results show that physical observation of the micro-architecture can lead to improved attacks