International Association
for Cryptologic Research

Persistent faults mark a new class of injections that perturb lookup tables within block ciphers with the overall goal of recovering the encryption key. Unlike earlier fault types persistent faults remain intact over many encryptions until the affected device is rebooted, thus allowing an adversary to collect a multitude of correct and faulty ciphertexts. It was shown to be an efficient and effective attack against substitution-permutation networks. In this paper, the scope of persistent faults is further broadened and explored. More specifically, we show how to construct a key-recovery attack on generic Feistel schemes in the presence of persistent faults. In a second step, we leverage these faults to reverse-engineer AES- and PRESENT-like ciphers in a chosen-key setting, in which some of the computational layers, like substitution tables, are kept secret. Finally, we propose a novel, dedicated, and low-overhead countermeasure that provides adequate protection for hardware implementations against persistent fault injections.

In this paper, we study isogeny graphs of supersingular elliptic curves. Supersingular isogeny graphs were introduced as a hard problem into cryptography by Charles, Goren, and Lauter for the construction of cryptographic hash functions. These are large expander graphs, and the hard problem is to find an efficient algorithm for routing, or path-finding, between two vertices of the graph. We consider four aspects of supersingular isogeny graphs, study each thoroughly and, where appropriate, discuss how they relate to one another. First, we consider two related graphs that help us understand the structure: the `spine' $\mathcal{S}$, which is the subgraph of $\mathcal{G}_\ell(\overline{\mathbb{F}_p})$ given by the $j$-invariants in $\mathbb{F}_p$, and the graph $\mathcal{G}_\ell(\mathbb{F}_p)$, in which both curves and isogenies must be defined over $\mathbb{F}_p$. We show how to pass from the latter to the former. The graph $\mathcal{S}$ is relevant for cryptanalysis because routing between vertices in $\mathbb{F}_p$ is easier than in the full isogeny graph. The $\mathbb{F}_p$-vertices are typically assumed to be randomly distributed in the graph, which is far from true. We provide an analysis of the distances of connected components of $\mathcal{S}$.

Next, we study the involution on $\mathcal{G}_\ell(\overline{\mathbb{F}_p})$ that is given by the Frobenius of $\mathbb{F}_p$ and give heuristics on how often shortest paths between two conjugate $j$-invariants are preserved by this involution (mirror paths). We also study the related question of what proportion of conjugate $j$-invariants are $\ell$-isogenous for $\ell = 2,3$. We conclude with experimental data on the diameters of supersingular isogeny graphs when $\ell = 2$ and compare this with previous results on diameters of LPS graphs and random Ramanujan graphs.

Dynamic Searchable Symmetric Encryption (DSSE) enables a client to perform updates and searches on encrypted data which makes it very useful in practice. To protect DSSE from the leakage of updates (leading to break query or data privacy), two new security notions, forward and backward privacy, have been proposed recently. Although extensive attention has been paid to forward privacy, this is not the case for backward privacy. Backward privacy, first formally introduced by Bost et al., is classified into three types from weak to strong, exactly Type-III to Type-I. To the best of our knowledge, however, no practical DSSE schemes without trusted hardware (e.g. SGX) have been proposed so far, in terms of the strong backward privacy and constant roundtrips between the client and the server.

In this work, we present a new DSSE scheme by leveraging simple symmetric encryption with homomorphic addition and bitmap index. The new scheme can achieve both forward and backward privacy with one roundtrip. In particular, the backward privacy we achieve in our scheme (denoted by Type-I$^-$) is somewhat stronger than Type-I. Moreover, our scheme is very practical as it involves only lightweight cryptographic operations. To make it scalable for supporting billions of files, we further extend it to a multi-block setting. Finally, we give the corresponding security proofs and experimental evaluation which demonstrate both security and practicality of our schemes, respectively.

The Holy Grail of a decentralised stablecoin is achieved on rigorous mathematical frameworks, obtaining multiple advantageous proofs: stability, convergence, truthfulness, faithfulness, and malicious-security. These properties could only be attained by the novel and interdisciplinary combination of previously unrelated fields: model predictive control, deep learning, alternating direction method of multipliers (consensus-ADMM), mechanism design, secure multi-party computation, and zero-knowledge proofs. For the first time, this paper proves:

- the feasibility of decentralising the central bank while securely preserving its independence in a decentralised computation setting

- the benefits for price stability of combining mechanism design, provable security, and control theory, unlike the heuristics of previous stablecoins

- the implementation of complex monetary policies on a stablecoin, equivalent to the ones used by central banks and beyond the current fixed rules of cryptocurrencies that hinder their price stability

- methods to circumvent the impossibilities of Guaranteed Output Delivery (G.O.D.) and fairness: standing on truthfulness and faithfulness, we reach G.O.D. and fairness under the assumption of rational parties

As a corollary, a decentralised artificial intelligence is able to conduct the monetary policy of a stablecoin, minimising human intervention.

Memory fault attacks, inducing errors in computations, have been an ever-evolving threat to cryptographic schemes since their discovery for cryptography by Boneh et al. (Eurocrypt 1997). Initially requiring physical tampering with hardware, the software-based rowhammer attack put forward by Kim et al. (ISCA 2014) enabled fault attacks also through malicious software running on the same host machine. This lead to concerning novel attack vectors, for example on deterministic signature schemes, whose approach to avoid dependency on (good) randomness renders them vulnerable to fault attacks. This has been demonstrated in realistic adversarial settings in a series of recent works. However, a unified formalism of different memory fault attacks, enabling also to argue the security of countermeasures, is missing yet.

In this work, we suggest a generic extension for existing security models that enables a game-based treatment of cryptographic fault resilience. Our modeling specifies exemplary memory fault attack types of different strength, ranging from random bit-flip faults to differential (rowhammer-style) faults to full adversarial control on indicated memory variables. We apply our model first to deterministic signatures to revisit known fault attacks as well as to establish provable guarantees of fault resilience for proposed fault-attack countermeasures. In a second application to nonce-misuse resistant authenticated encryption, we provide the first fault-attack treatment of the SIV mode of operation and give a provably secure fault-resilient variant.

This paper presents two new improved attacks on the KMOV cryptosystem. KMOV is an encryption algorithm based on elliptic curves over the ring ${\mathbb{Z}}_N$ where $N=pq$ is a product of two large primes of equal bit size. The first attack uses the properties of the convergents of the continued fraction expansion of a specific value derived from the KMOV public key. The second attack is based on Coppersmith's method for finding small solutions of a multivariate polynomial modular equation. Both attacks improve the existing attacks on the KMOV cryptosystem.

The elliptic curve cryptography plays a central role in various cryptographic schemes and protocols. For efficiency reasons, Edwards curves and twisted Edwards curves have been introduced. In this paper, we study the properties of twisted Edwards curves on the ring $\mathbb{Z}/n\mathbb{Z}$ where $n=p^rq^s$ is a prime power RSA modulus and propose a new scheme and study its efficiency and security.

Let $N=pq$ be an RSA modulus and $e$ be a public exponent. Numerous attacks on RSA exploit the arithmetical properties of the key equation $ed-k(p-1)(q-1)=1$. In this paper, we study the more general equation $eu-(p-s)(q-r)v=w$. We show that when the unknown integers $u$, $v$, $w$, $r$ and $s$ are suitably small and $p-s$ or $q-r$ is factorable using the Elliptic Curve Method for factorization ECM, then one can break the RSA system. As an application, we propose an attack on Demytko's elliptic curve cryptosystem. Our method is based on Coppersmith's technique for solving multivariate polynomial modular equations.

We present CrypTFlow, a first of its kind system that converts TensorFlow inference code into Secure Multi-party Computation (MPC) protocols at the push of a button. To do this, we build three components. Our first component, Athos, is an end-to-end compiler from TensorFlow to a variety of semi-honest MPC protocols. The second component, Porthos, is an improved semi-honest 3-party protocol that provides significant speedups for Tensorflow like applications. Finally, to provide malicious secure MPC protocols, our third component, Aramis, is a novel technique that uses hardware with integrity guarantees to convert any semi-honest MPC protocol into an MPC protocol that provides malicious security. The security of the protocols output by Aramis relies on hardware for integrity and MPC for confidentiality. Moreover, our system, through the use of a new float-to-fixed compiler, matches the inference accuracy over the plaintext floating-point counterparts of these networks.

We experimentally demonstrate the power of our system by showing the secure inference of real-world neural networks such as ResNet50, DenseNet121, and SqueezeNet over the ImageNet dataset with running times of about 30 seconds for semi-honest security and under two minutes for malicious security. Prior work in the area of secure inference (SecureML, MiniONN, HyCC, ABY$^3$, CHET, EzPC, Gazelle, and SecureNN) has been limited to semi-honest security of toy networks with 3--4 layers over tiny datasets such as MNIST or CIFAR which have 10 classes. In contrast, our largest network has 200 layers, 65 million parameters and over 1000 ImageNet classes. Even on MNIST/CIFAR, CrypTFlow outperforms prior work.

In the article we propose a new compression method (to $2\log_2(p) + 3$ bits) for the $\mathbb{F}_{\!p^2}$-points of an elliptic curve $E_b\!: y^2 = x^3 + b$ (for $b \in \mathbb{F}_{\!p^2}^*$) of $j$-invariant $0$. It is based on $\mathbb{F}_{\!p}$-rationality of some generalized Kummer surface $GK_b$. This is the geometric quotient of the Weil restriction $R_b := \mathrm{R}_{\: \mathbb{F}_{\!p^2}/\mathbb{F}_{\!p}}(E_b)$ under the order $3$ automorphism restricted from $E_b$. More precisely, we apply the theory of conic bundles (i.e., conics over the function field $\mathbb{F}_{\!p}(t)$) to obtain explicit and quite simple formulas of a birational $\mathbb{F}_{\!p}$-isomorphism between $GK_b$ and $\mathbb{A}^{\!2}$. Our point compression method consists in computation of these formulas. To recover (in the decompression stage) the original point from $E_b(\mathbb{F}_{\!p^2}) = R_b(\mathbb{F}_{\!p})$ we find an inverse image of the natural map $R_b \to GK_b$ of degree $3$, i.e., we extract a cubic $\mathbb{F}_{\!p}$-root. For $p \not\equiv 1 \: (\mathrm{mod} \ 27)$ this is just a single exponentiation in $\mathbb{F}_{\!p}$, hence the new method seems to be much faster than the classical one with $x$ coordinate, which requires two exponentiations in $\mathbb{F}_{\!p}$. In particular, it is perfectly applicable to pairing-friendly elliptic curves from one IETF-draft and to those used in the cryptocurrencies Ethereum and Zcash.

We present a methodology to construct preprocessing zkSNARKs where the structured reference string (SRS) is universal and updatable. This exploits a novel use of *holography* [Babai et al., STOC 1991], where fast verification is achieved provided the statement being checked is given in encoded form.

We use our methodology to obtain a preprocessing zkSNARK where the SRS has linear size and arguments have constant size. Our construction improves on Sonic [Maller et al., CCS 2019], the prior state of the art in this setting, in all efficiency parameters: proving is an order of magnitude faster and verification is thrice as fast, even with smaller SRS size and argument size. Our construction is most efficient when instantiated in the algebraic group model (also used by Sonic), but we also demonstrate how to realize it under concrete knowledge assumptions. We implement and evaluate our construction.

The core of our preprocessing zkSNARK is an efficient *algebraic holographic proof* (AHP) for rank-1 constraint satisfiability (R1CS) that achieves linear proof length and constant query complexity.

The task of function inversion is central to cryptanalysis: breaking block ciphers, forging signatures, and cracking password hashes are all special cases of the function-inversion problem. In 1980, Hellman showed that it is possible to invert a random function $f\colon [N] \to [N]$ in time $T = \widetilde{O}(N^{2/3})$ given only $S = \widetilde{O}(N^{2/3})$ bits of precomputed advice about $f$. Hellman’s algorithm is the basis for the popular “Rainbow Tables” technique (Oechslin, 2003), which achieves the same asymptotic cost and is widely used in practical cryptanalysis.

Is Hellman’s method the best possible algorithm for inverting functions with preprocessed advice? The best known lower bound, due to Yao (1990), shows that $ST = \widetilde{\Omega}(N)$, which still admits the possibility of an $S = T = \widetilde{O}(N^{1/2})$ attack. There remains a long-standing and vexing gap between Hellman’s $N^{2/3}$ upper bound and Yao’s $N^{1/2}$ lower bound. Understanding the feasibility of an $S = T = N^{1/2}$ algorithm is cryptanalytically relevant since such an algorithm could perform a key-recovery attack on AES-128 in time $2^{64}$ using a precomputed table of size $2^{64}$.

For the past 29 years, there has been no progress either in improving Hellman’s algorithm or in strengthening Yao’s lower bound. In this work, we connect function inversion to problems in other areas of theory to (1) explain why progress may be difficult and (2) explore possible ways forward.

Our results are as follows:

- We show that *any* improvement on Yao’s lower bound on function-inversion algorithms will imply new lower bounds on depth-two circuits with arbitrary gates. Further, we show that proving strong lower bounds on *non-adaptive* function-inversion algorithms would imply breakthrough circuit lower bounds on linear-size log-depth circuits.

- We take first steps towards the study of the *injective* function-inversion problem, which has manifold cryptographic applications. In particular, we show that improved algorithms for breaking PRGs with preprocessing would give improved algorithms for inverting injective functions with preprocessing.

- Finally, we show that function inversion is closely related to well-studied problems in communication complexity and data structures. Through these connections we immediately obtain the best known algorithms for problems in these domains.

In predicate encryption for a function $f$, an authority can create ciphertexts and secret keys which are associated with `attributes'. A user with decryption key $K_y$ corresponding to attribute $y$ can decrypt a ciphertext $CT_x$ corresponding to a message $m$ and attribute $x$ if and only if $f(x,y)=0$. Furthermore, the attribute $x$ remains hidden to the user if $f(x,y) \neq 0$.

We construct predicate encryption from assumptions on bilinear maps for a large class of new functions, including sparse set disjointness, Hamming distance at most $k$, inner product mod 2, and any function with an efficient Arthur-Merlin communication protocol. Our construction uses a new probabilistic representation of Boolean functions we call `one-sided probabilistic rank,' and combines it with known constructions of inner product encryption in a novel way.

In a recent work, Garg, Hajiabadi, Mahmoody, and Rahimi (TCC 18) introduced a new encryption framework, which they referred to as Registration-Based Encryption (RBE). The central motivation behind RBE was to provide a novel methodology for solving the well-known key-escrow problem in Identity-Based Encryption (IBE) systems. Informally, in an RBE system there is no private-key generator unlike IBE systems, but instead it is replaced with a public key accumulator. Every user in an RBE system samples its own public-secret key pair, and sends the public key to the accumulator for registration. The key accumulator has no secret state, and is only responsible for compressing all the registered user identity-key pairs into a short public commitment. Here the encryptor only requires the compressed parameters along with the target identity, whereas a decryptor requires supplementary key material along with the secret key associated with the registered public key.

The initial construction by Garg et al. (TCC 18) based on standard assumptions only provided weak efficiency properties. In a follow-up work by Garg, Hajiabadi, Mahmoody, Rahimi, and Sekar (PKC 19), they gave an efficient RBE construction from standard assumptions. However, both these works considered the key accumulator to be honest which might be too strong an assumption in real-world scenarios. In this work, we initiate a formal study of RBE systems with malicious key accumulators. To that end, we introduce a strengthening of the RBE framework which we call Verifiable RBE (VRBE). A VRBE system additionally gives the users an extra capability to obtain short proofs from the key accumulator proving correct (and unique) registration for every registered user as well as proving non-registration for any yet unregistered identity.

We construct VRBE systems which provide succinct proofs of registration and non-registration from standard assumptions (such as CDH, Factoring, LWE). Our proof systems also naturally allow a much more efficient audit process which can be perfomed by any non-participating third party as well. A by-product of our approach is that we provide a more efficient RBE construction than that provided in the prior work of Garg et al. (PKC 19). And, lastly we initiate a study on extension of VRBE to a wider range of access and trust structures.

Bluetooth is a widely deployed standard for wireless communications between mobile devices. It uses authenticated Elliptic Curve Diffie-Hellman for its key exchange. In this paper we show that the authentication provided by the Bluetooth pairing protocols is insufficient and does not provide the promised MitM protection. We present a new attack that modifies the y-coordinates of the public keys (while preserving the x-coordinates). The attack compromises the encryption keys of all of the current Bluetooth authenticated pairing protocols, provided both paired devices are vulnerable. Specifically, it successfully compromises the encryption keys of 50% of the Bluetooth pairing attempts, while in the other 50% the pairing of the victims is terminated. The affected vendors have been informed and patched their products accordingly, and the Bluetooth specification had been modified to address the new attack. We named our new attack the “Fixed Coordinate Invalid Curve Attack”. Unlike the well known “Invalid Curve Attack” of Biehl et. al. which recovers the private key by sending multiple specially crafted points to the victim, our attack is a MitM attack which modifies the public keys in a way that lets the attacker deduce the shared secret.

We present a machine-checked proof of security for the domain management protocol of Amazon Web Services' KMS (Key Management Service) a critical security service used throughout AWS and by AWS customers. Domain management is at the core of AWS KMS; it governs the top-level keys that anchor the security of encryption services at AWS. We show that the protocol securely implements an ideal distributed encryption mechanism under standard cryptographic assumptions. The proof is machine-checked in the EasyCrypt proof assistant and is the largest EasyCrypt development to date.

Vehicular Ad-hoc Networks (VANETs) are a cardinal part of intelligent transportation system (ITS) which render various services in terms of traffic and transport management. The VANET is used to manage growing traffic and manage data about traffic conditions, weather, road conditions, speed of the vehicle, etc. Even though, VANETs are self-sufficient and effective networks but they still suffer from various security and privacy issues. VANETs need to ensure that an adversary should not be able to breach user associated data and delete or modify the exchanged messages for its gains, as these messages comprise of sensitive data. In this paper, we have proposed an authentication and key-agreement protocol based on cryptographic hash functions which makes it lightweight in nature and also suitable for VANET environment. Moreover, to enhance the security and reliability of the entire system, the proposed key-agreement protocol makes use of random session modulus to compute a dynamic session key i.e. for every session, vehicles generate their session specific secret modulus which are then converged to form a common group session key. The formal verification of the proposed work is done using Real - or - Random oracle model, AVISPA and BAN Logic while informal security analysis shows that the proposed protocol can withstand various attacks. The simulation results and analysis prove that the proposed work is efficient and has a real-time application in VANET environment.

Existing logic obfuscation approaches aim to protect hardware design IPs from SAT attack by increasing query count and output corruptibility of a locked netlist. In this paper, we demonstrate the ineffectiveness of such techniques to obfuscate hardware accelerator platforms. Subsequently, we propose a Hardware/software co-design based Accelerator Obfuscation (HSCAO) scheme to provably safeguard the IP of such designs against SAT as well as removal/bypass type of attacks while still maintaining high output corruptability for applications. The attack resiliency of HSCAO scheme is manifested by using a sequence of keys to obfuscate instruction encoding for an application. Experimental evaluations utilizing an accelerator simulator demonstrate the effectiveness of our proposed countermeasure.

With the burgeoning Vehicle-to-Everything (V2X) communication, security and privacy concerns are paramount. Such concerns are usually mitigated by combining cryptographic mechanisms with suitable key management architecture. However, cryptographic operations may be quite resource-intensive, placing a considerable burden on the vehicle’s V2X computing unit. To assuage this issue, it is reasonable to use hardware acceleration for common cryptographic primitives, such as block ciphers, digital signature schemes, and key exchange protocols. In this scenario, custom extension instructions can be a plausible option, since they achieve fine-tune hardware acceleration with a low to moderate logic overhead, while also reducing code size. In this article, we apply this method along with dual-data memory banks for the hardware acceleration of the PRESENT block cipher, as well as for the $F_{2^{255}-19}$ finite field arithmetic employed in cryptographic primitives based on Curve25519 (e.g., EdDSA and X25519). As a result, when compared with a state-of-the-art software-optimized implementation, the performance of PRESENT is improved by a factor of 17 to 34 and code size is reduced by 70%, with only a 4.37% increase in FPGA logic overhead. In addition, we improve the performance of operations over Curve25519 by a factor of ~2.5 when compared to an Assembly implementation on a comparable processor, with moderate logic overhead (namely, 9.1%). Finally, we achieve significant performance gains in the V2X provisioning process by leveraging our hardware-accelerated cryptographic primitives

Event date: 15 April to 17 April 2020
Submission deadline: 26 November 2019
Notification: 20 January 2020