International Association
for Cryptologic Research

Secure computation is a cornerstone of modern cryptography and a rich body of research is devoted to understanding its round complexity. In this work, we consider two-party computation (2PC) protocols (where both parties receive output) that remain secure in the realistic setting where many instances of the protocol are executed in parallel (concurrent security). We obtain a two-round concurrent-secure 2PC protocol based on a single, standard, post-quantum assumption: The subexponential hardness of the learning-with-errors (LWE) problem. Our protocol is in the plain model, i.e., it has no trusted setup, and it is secure in the super-polynomial simulation framework of Pass (EUROCRYPT 2003). Since two rounds are minimal for (concurrent) 2PC, this work resolves the round complexity of concurrent 2PC from standard assumptions. As immediate applications, our work establishes feasibility results for interesting cryptographic primitives such as The first two-round password authentication key exchange (PAKE) protocol in the plain model and the first two-round concurrent secure computation protocol for quantum circuits (2PQC).

An Identity-based matchmaking encryption (IB-ME) scheme proposed at CRYPTO 2019 supports anonymous but authenticated communications in a way that communication parties can both specify the senders or receivers on the fly. IB-ME is easy to be used in several network applications requiring privacy-preserving for its efficient implementation and special syntax. In the literature, IB-ME schemes are built from the variants of Diffie-Hellman assumption and all fail to retain security for quantum attackers. Despite the rigorous security proofs in previous security models, the existing schemes are still possibly vulnerable to some potential neglected attacks. Aiming at the above problems, we provide stronger security definitions considering new attacks to fit real-world scenarios and then propose a generic construction of IB-ME satisfying the new model. Inspired by the prior IB-ME construction of Chen et al., the proposed scheme is constructed by combining 2-level anonymous hierarchical IBE (HIBE) and identity-based signature (IBS) schemes. In order to upgrade lattice-based IB-ME with better efficiency, we additionally improve a lattice IBS, as an independent technical contribution, to shorten its signature and thus reduce the final IB-ME ciphertext size. By combining the improved IBS and any 2-level adaptively-secure lattice-based HIBE with anonymity, we finally obtain the first IB-ME from lattices.

As digital tokens on blockchains such as non-fungible tokens (NFTs) increase in popularity and scale, the existing interfaces (ERC-721, ERC-20, and many more) are being exposed for being expensive and not scalable. As a result, tokens are being forced to be implemented on alternative blockchains where it is cheaper but less secure. To offer a solution without making security tradeoffs, we propose using joint cryptographic accumulators (e.g. joint Merkle trees). We propose a method of creating such joint accumulators in a decentralized fashion which is secured by the same set of validating nodes as existing blockchains. Such accumulators allow the tokens for certain applications to be implemented using up to 99.99% less of the blockchain’s resources by outsourcing most of the storage and computational requirements to the users creating the tokens. This is done without sacrificing permanence and verifiability of these tokens. This system achieves optimizations mainly by allowing certain storage of a blockchain to be used in a cross-application manner, instead of a per-application manner. Additionally, we show how it can be beneficial in other areas like privacy-preserving timestamps or shortening file hashes

To mitigate cybersecurity breaches, secure communication is crucial for the Internet of Things (IoT) environment. Data integrity is one of the most significant characteristics of security, which can be achieved by employing cryptographic hash functions. In view of the demand from IoT applications, the National Institute of Standards and Technology (NIST) initiated a standardization process for lightweight hash functions. This work presents field-programmable gate array (FPGA) implementations and carefully worked out optimizations of four Round-3 finalists in the NIST standardization process. A novel compact PHOTON-Beetle implementation is proposed wherein the underlying matrix multiplication is executed in serialized fashion to achieve a small hardware footprint. SPARKLE implementations are carried out by implementing the ARX-box in serialized, parallelized, and hybrid approaches. For Ascon and XOODYAK, the proposed implementations compute certain permutation rounds in one clock cycle in order to explore the trade-off between computation time and hardware area. As a result, this work achieves the smallest hardware footprint for PHOTON-Beetle consuming an area 3.4× smaller than state-of-the-art implementations. Ascon and XOODYAK are implemented in a flexible manner that achieves throughput-to-area (TP/A) ratios 1.8× and 3.9× higher, respectively, compared to implementations found in the literature. In addition, we propose the first FPGA implementations for the SPARKLE hash function. These efficient implementations provide guidelines for choosing a suitable architecture for applications in demand that can be employed in the IoT environment to achieve data integrity for various applications.

We present an algebraic attack on a McEliece-like scheme based on BCH codes (BCH-McEliece), where the Goppa code is replaced by a suitably permuted BCH code. Our attack continues the line of work devising attacks against McEliece-like schemes with Goppa-like codes, with the goal of getting a better understanding of why Goppa codes are so intractable. Our starting point is the work of Faugère, Perret and Portzamparc (Asiacrypt 2014). We take their algebraic model and adapt and improve their attack algorithm so that it can handle BCH-McEliece. We implement the attack and exhibit a parameter range where our attack is practical while generic attacks suggest cryptographic security.

The Meet-in-the-Middle (MitM) attack has been widely applied to preimage attacks on Merkle-Damg{\aa}rd (MD) hashing. In this paper, we introduce a generic framework of the MitM attack on sponge-based hashing. We find certain bit conditions can significantly reduce the diffusion of the unknown bits and lead to longer MitM characteristic. To find good or optimal configurations of MitM attacks, e.g., the bit conditions, the neutral sets, and the matching points, we introduce the bit-level MILP-based automatic tools on Keccak, Ascon and Xoodyak. To reduce the scale of bit-level models and make them solvable in reasonable time, a series of properties of the targeted hashing are considered in the modelling, such as the linear structure and CP-kernel for Keccak, the Boolean expression of Sbox for Ascon. Finally, we give an improved 4-round preimage attack on Keccak-512/SHA3, and break a nearly 10 years’ cryptanalysis record. We also give the first preimage attacks on 3-/4-round Ascon-XOF and 3-round Xoodyak-XOF.

CRYSTALS-Kyber has been selected by the NIST as a public-key encryption and key encapsulation mechanism to be standardized. It is also included in the NSA's suite of cryptographic algorithms recommended for national security systems. This makes it important to evaluate the resistance of CRYSTALS-Kyber's implementations to side-channel attacks. The unprotected and first-order masked software implementations have been already analysed. In this paper, we present deep learning-based message recovery attacks on the $\omega$-order masked implementations of CRYSTALS-Kyber in ARM Cortex-M4 CPU for $\omega \leq 5$. The main contribution is a new neural network training method called recursive learning. In the attack on an $\omega$-order masked implementation, we start training from an artificially constructed neural network $M^{\omega}$ whose weights are partly copied from a model $M^{\omega-1}$ trained on the $(\omega-1)$-order masked implementation, and then extended to one more share. Such a method allows us to train neural networks that can recover a message bit with the probability above 99% from high-order masked implementations.

TLS is ubiquitous in modern computer networks. It secures transport for high-end desktops and low-end embedded devices alike. However, the public key cryptosystems currently used within TLS may soon be obsolete as large-scale quantum computers, once realized, would be able to break them. This threat has led to the development of post-quantum cryptography (PQC). The U.S. standardization body NIST is currently in the process of concluding a multi-year search for promising post-quantum signature schemes and key encapsulation mechanisms (KEMs). With the first PQC standards around the corner, TLS will have to be updated soon. However, especially for small microcontrollers, it appears the current NIST post-quantum signature finalists pose a challenge. Dilithium suffers from very large public keys and signatures; while Falcon has significant hardware requirements for efficient implementations.

KEMTLS is a proposal for an alternative TLS handshake protocol that avoids authentication through signatures in the TLS handshake. Instead, it authenticates the peers through long-term KEM keys held in the certificates. The KEMs considered for standardization are more efficient in terms of computation and/or bandwidth than the post-quantum signature schemes.

In this work, we compare KEMTLS to TLS 1.3 in an embedded setting. To gain meaningful results, we present implementations of KEMTLS and TLS 1.3 on a Cortex-M4-based platform. These implementations are based on the popular WolfSSL embedded TLS library and hence share a majority of their code. In our experiments, we consider both protocols with the remaining NIST finalist signature schemes and KEMs, except for Classic McEliece which has too large public keys. Both protocols are benchmarked and compared in terms of run-time, memory usage, traffic volume and code size. The benchmarks are performed in network settings relevant to the Internet of Things, namely low-latency broadband, LTE-M and Narrowband IoT. Our results show that KEMTLS can reduce handshake time by up to 38%, can lower peak memory consumption and can save traffic volume compared to TLS 1.3.

Nonces are a fact of life for achieving semantic security. Generating a uniformly random nonce can be costly and may not always be feasible. Using anything other than uniformly random bits can result in information leakage; e.g., a timestamp can deanonymize a communication and a counter can leak the quantity of transmitted messages. Ideally, we would like to be able to efficiently encrypt the nonce to 1) avoid needing uniformly random bits and 2) avoid information leakage. This paper presents two new authenticated encryption modes built on top of Farfalle that perfectly achieve these goals.

The building blocks for secure messaging apps, such as Signal's X3DH and Double Ratchet (DR) protocols, have received a lot of attention from the research community. They have notably been proved to meet strong security properties even in the case of compromise such as Forward Secrecy (FS) and Post-Compromise Security (PCS). However, there is a lack of formal study of these properties at the application level. Whereas the research works have studied such properties in the context of a single ratcheting chain, a conversation between two persons in a messaging application can in fact be the result of merging multiple ratcheting chains. In this work, we initiate the formal analysis of secure messaging taking the session-handling layer into account, and apply our approach to Sesame, Signal's session management. We first experimentally show practical scenarios in which PCS can be violated in Signal by a clone attacker, despite its use of the Double Ratchet. We identify exactly how this is enabled by Signal's session-handling layer. We then design a formal model of the session-handling layer of Signal that is tractable for automated verification with the Tamarin prover, and use this model to rediscover the PCS violation and propose two provably secure fixes to offer stronger guarantees.

Asynchronous Byzantine fault-tolerant (BFT) protocols have received increasing attention, as they are particularly robust against timing and performance attacks. This paper designs and implements Dory, an asynchronous BFT protocol with reduced communication and improved efficiency compared to existing systems. In particular, Dory reduces the communication both asymptotically and concretely and gains in improved performance. To achieve the goal, we have devised a novel primitive called asynchronous vector data dissemination, and we have developed the idea of supplemental consensus originally used in DispersedLedger for higher throughput and fairness without using threshold encryption.

We have implemented and deployed our system using up to 151 replicas on Amazon EC2. We demonstrate that even without using the technique of separating data transmission from agreement, Dory has up to 5x the throughput of Speeding Dumbo (sDumbo), while lowering the communication cost for different batch sizes.

Self-sovereign identity (SSI) systems have gained increasing attention over the last five years. In a variety of fields (e.g., education, IT security, law, government), developers and researchers are attempting to give end-users back their right to and control of their data. Although prototypes and theoretical concepts for SSI applications exist, the majority of them are still in their infancy. Due to missing definitions and standards, there is currently a lack of common understanding of SSI system within the (IT) community.

To investigate current commonalities and differences in SSI understanding, I contribute the first qualitative user study (N=13) on expert mental models of SSI and its associated threat landscape. The study results highlight the need for a general definition of SSI and further standards for such systems, as experts' perceptions of SSI requirements vary widely. Based on the expert interviews, I constructed a minimal knowledge map for (potential) SSI end-users and formulated design guidelines for SSI to facilitate broad adoption in the wild and improve privacy-preserving usage.

Function Secret Sharing (FSS; Eurocrypt 2015) allows a dealer to share a function f with two or more evaluators. Given secret shares of a function f, the evaluators can locally compute secret shares of f(x) on an input x, without learning information about f.

In this paper, we initiate the study of access control for FSS. Given the shares of f, the evaluators can ensure that the dealer is authorized to share the provided function. For a function family F and an access control list defined over the family, the evaluators receiving the shares of f ∈ F can efficiently check that the dealer knows the access key for f.

This model enables new applications of FSS, such as: – anonymous authentication in a multi-party setting, – access control in private databases, and – authentication and spam prevention in anonymous communication systems.

Our definitions and constructions abstract and improve the concrete efficiency of several re- cent systems that implement ad-hoc mechanisms for access control over FSS. The main building block behind our efficiency improvement is a discrete-logarithm zero-knowledge proof-of-knowledge over secret-shared elements, which may be of independent interest.

We evaluate our constructions and show a 50–70× reduction in computational overhead com- pared to existing access control techniques used in anonymous communication. In other applications, such as private databases, the processing cost of introducing access control is only 1.5–3× when amortized over databases with 500,000 or more items.

Recently, the results of the NIST PQC contest were announced. Classic McEliece, one of the 3rd round candidates, was selected as the fourth round candidate. Classic McEliece is the only code-based cipher in the NIST PQC finalists in third round and the algorithm is regarded as secure. However, it has low efficiency. In this paper, we propose an efficient software implementation of Classic McEliece, a code-based cipher, on 64-bit ARMv8 processors. Classic McEliece can be divided into Key Generation, Encapsulation, and Decapsulation. Among them, we propose an optimal implementation for Encapsulation and Decapsulation. Optimized Encapsulation implementation utilizes vector registers to perform 16-byte parallel operations, and optimize using the specificity of the identity matrix. Decapsulation implemented efficient Multiplication and Inversion on $F_2^m$ field. Compared with the previous results, Encapsulation showed the performance improvement of up-to 1.99× than the-state-of-art works.

EDHOC is a lightweight authenticated key exchange protocol for IoT communication, currently being standardized by the IETF. Its design is a trimmed-down version of similar protocols like TLS 1.3, building on the SIGn-then-MAc (SIGMA) rationale. In its trimming, however, EDHOC notably deviates from the SIGMA design by sending only short, non-unique credential identifiers, and letting recipients perform trial verification to determine the correct communication partner. Done naively, this can lead to identity misbinding attacks when an attacker can control some of the user keys, invalidating the original SIGMA security analysis and contesting the security of EDHOC.

In this work, we formalize a multi-stage key exchange security model capturing the potential attack vectors introduced by non-unique credential identifiers. We show that EDHOC, in its draft version 17, indeed achieves session key security and user authentication even in a strong model where the adversary can register malicious keys with colliding identifiers, given that the employed signature scheme provides so-called exclusive ownership. Through our security result, we confirm cryptographic improvements integrated by the IETF working group in recent draft versions of EDHOC based on recommendations from our and others' analysis.

We give two applications of the "embedding Lemma". The first one is a polynomial time (in $\log q$) algorithm to compute the endomorphism ring $\mathrm{End}(E)$ of an ordinary elliptic curve $E/\mathbb{F}_q$, provided we are given the factorisation of $Δ_π$.

The second application is an algorithm to compute the canonical lift of $E/\mathbb{F}_q$, $q=p^n$, (still assuming that $E$ is ordinary) to precision $m$ in time $\tilde{O}(n m \log^{O(1)} p)$. We deduce a point counting algorithm of complexity $\tilde{O}(n^2 \log^{O(1)} p)$. In particular the complexity is polynomial in $\log p$, by contrast of what is usually expected of a $p$-adic cohomology computation. This algorithm generalizes to ordinary abelian varieties.

A (single server) private information retrieval (PIR) allows a client to read data from a public database held on a remote server, without revealing to the server which locations she is reading. In a doubly efficient PIR (DEPIR), the database is first preprocessed, but the server can subsequently answer any client's query in time that is sub-linear in the database size. Prior work gave a plausible candidate for a public-key variant of DEPIR, where a trusted party is needed to securely preprocess the database and generate a corresponding public key for the clients; security relied on a new non-standard code-based assumption and a heuristic use of ideal obfuscation. In this work we construct the stronger unkeyed notion of DEPIR, where the preprocessing is a deterministic procedure that the server can execute on its own. Moreover, we prove security under just the standard ring learning-with-errors (RingLWE) assumption. For a database of size $N$ and any constant $\varepsilon>0$, the preprocessing run-time and size is $O(N^{1+\varepsilon})$, while the run-time and communication-complexity of each PIR query is $polylog(N)$. We also show how to update the preprocessed database in time $O(N^\varepsilon)$. Our approach is to first construct a standard PIR where the server's computation consists of evaluating a multivariate polynomial; we then convert it to a DEPIR by preprocessing the polynomial to allow for fast evaluation, using the techniques of Kedlaya and Umans (STOC '08).

Building on top of our DEPIR, we construct general fully homomorphic encryption for random-access machines (RAM-FHE), which allows a server to homomorphically evaluate an arbitrary RAM program $P$ over a client's encrypted input $x$ and the server's preprocessed plaintext input $y$ to derive an encryption of the output $P(x,y)$ in time that scales with the RAM run-time of the computation rather than its circuit size. Prior work only gave a heuristic candidate construction of a restricted notion of RAM-FHE. In this work, we construct RAM-FHE under the RingLWE assumption with circular security. For a RAM program $P$ with worst-case run-time $T$, the homomorphic evaluation runs in time $T^{1+\varepsilon} \cdot polylog(|x| + |y|)$.

To achieve semantic security, symmetric encryption schemes classically require ciphertext expansion. In this paper we provide a means to achieve semantic security while preserving the length of messages at the cost of mildly sacrificing correctness. Concretely, we propose a new scheme that can be interpreted as a secure alternative to (or wrapper around) plain Electronic Codebook (ECB) mode of encryption, and for this reason we name it Secure Codebook (SCB). Our scheme is the first length-preserving encryption scheme to effectively achieve semantic security.

This paper presents a new method for quantum identity authentication (QIA) protocols. The logic of classical zero-knowledge proofs (ZKPs) due to Schnorr is applied in quantum circuits and algorithms. This novel approach gives an exact way with which a prover $P$ can prove they know some secret without transmitting that directly to a verifier $V$ by means of a quantum channel - allowing for a ZKP wherein an eavesdropper or manipulation can be detected with a 'fail safe' design. With the anticipated advent of a 'quantum internet', such protocols and ideas may soon have utility and execution in the real world.

Internet of vehicles (IoV) has brought technological revolution in the fields of intelligent transport system and smart cities. With the rise in self-driven cars and AI managed traffic system, threats to such systems have increased significantly. There is an immediate need to mitigate such attacks and ensure security, trust and privacy. Any malfunctioning or misbehaviour in an IoV based system can lead to fatal accidents. This is because IoV based systems are sensitive in nature involving human lives either on or off the roads. Any compromise to such systems can affect user safety and incur in service delays. For IoV users, the Intrusion Detection System (IDS) is crucial to protect them from different malware-based attacks and to ensure the security of users and infrastructures. Machine Learning approaches are used for extracting useful features from network traffic and also for predicting the patterns of anomalous activities. We use two datasets, namely Balanced DDoS dataset and Car-Hacking Dataset for comparative study of intrusion detection using various machine learning approaches. The comparative study shows the differences of various machine learning and deep learning approaches against two datasets.