International Association
for Cryptologic Research

The Center for Cyber Security and Privacy of the University of Birmingham is looking for a postdoctoral researcher in cryptography. We invite applications from candidates with research records in applied probability and security reductions/analysis of cryptographic schemes. The position is for 1 year. For informal enquiries, please contact Rishiraj Bhattacharyya.

Closing date for applications:

Contact: Rishiraj Bhattacharyya (r.bhattacharyya@bham.ac.uk)

More information: https://edzz.fa.em3.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_6001/job/3750/

Limitless Labs is an R&D collective advancing gaming, distributed systems & computing. Our team has extensive expertise in fields like cryptography, crypto networks, game development, ML, product growth & startups. In the past, our founding team has been 2x backed by a16z, built an AI app company with 250M downloads, a prominent web3 gaming title and reached half a million people around the world with blockchain-powered humanitarian relief.

This role is dedicated to applied research. In our initial phases, we are committed to understanding and leveraging the state-of-the-art, while in future phases, we will advance it. Primarily, the researcher will contribute to the design of new architectural solutions.

Responsibilities

- Design, specify and verify distributed systems by leveraging formal and experimental techniques.

- Build proof of concepts and prepare executable specifications for the development team.

- Regularly going through papers, bringing new ideas and staying up-to-date.

- Conducting theoretical and practical analysis of the performance of distributed systems.

- Collaborating with both internal and external contributors.

Closing date for applications:

Contact: Ira | Head of People @ Limitless Labs

More information: https://apply.workable.com/limitless-labs-network/j/EF6246F619/

Anonymous systems are susceptible to malicious activity. For instance, in anonymous payment systems, users may engage in illicit practices like money laundering. Similarly, anonymous federated learning systems decouple user updates to a central machine learning model from the user's identity; malicious users can manipulate their updates to poison the model. Today, compliance with system-generated rules in such systems can be guaranteed at the level of a single message by utilizing Zero-Knowledge Proofs (ZKP). However, it remains unclear how to prove compliance for rules that are defined over a collection of a user's messages, without compromising the unlinkability of the messages.

To address this challenge, we propose an efficient protocol called Shuffle-ZKP, which enables users within an unlinkable messaging system to collectively prove their compliance. Our protocol leverages a distributed and private set equality check protocol along with generic Non-Interactive Zero-Knowledge (NIZK) proof systems. We also provide an additional attributing protocol to identify misbehaving users. We theoretically analyze the protocol's correctness and privacy properties; we then implement and test it across multiple use cases. Our empirical results show that in use cases involving thousands of users, each user is able to generate a compliance proof within 0.2-10.6 seconds, depending on the use case, while the additional communication overhead remains under 3KB. Furthermore, the protocol is computationally efficient on the server side; the verification algorithm requires a few seconds to handle thousands of users in all of our use cases.

Collateral is an item of value serving as security for the repayment of a loan. In blockchain-based loans, cryptocurrencies serve as the collateral. The high volatility of cryptocurrencies implies a serious barrier of entry with a common practice that collateral values equal multiple times the value of the loan. As assets serving as collateral are locked, this requirement prevents many candidates from obtaining loans. In this paper, we aim to make loans more accessible by offering loans with lower collateral, while keeping the risk for lenders bound. We propose a credit score based on data recovered from the blockchain to predict how likely a potential borrower is to repay a loan. Our protocol does not risk the initial amount granted by liquidity providers, but only risks part of the interest yield gained from the borrower by the protocol in the past.

Blockchain interoperability refers to the ability of blockchains to share information with each other. Decentralized Exchanges (DEXs) are peer-to-peer marketplaces where traders can exchange cryptocurrencies. Several studies have focused on arbitrage analysis within a single blockchain, typically in Ethereum. Recently, we have seen a growing interest in cross-chain technologies to create a more interconnected blockchain network. We present a framework to study cross-chain arbitrage in DEXs. We use this framework to analyze cross-chain arbitrages between two popular DEXs, PancakeSwap and QuickSwap, within a time frame of a month. While PancakeSwap is implemented on a blockchain named BNB Chain, QuickSwap is implemented on a different blockchain named Polygon. The approach of this work is to study the cross-chain arbitrage through an empirical study. We refer to the number of arbitrages, their revenue as well as to their duration. This work lays the basis for understanding cross-chain arbitrage and its potential impact on the blockchain technology.

We present Private Random Access Computations (PRAC), a 3-party Secure Multi-Party Computation (MPC) framework to support random-access data structure algorithms for MPC with efficient communication in terms of rounds and bandwidth. PRAC extends the state-of-the-art DORAM Duoram with a new implementation, more flexibility in how the DORAM memory is shared, and support for Incremental and Wide DPFs. We then use these DPF extensions to achieve algorithmic improvements in three novel oblivious data structure protocols for MPC. PRAC exploits the observation that a secure protocol for an algorithm can gain efficiency if the protocol explicitly reveals information leaked by the algorithm inherently. We first present an optimized binary search protocol that reduces the bandwidth from $O(\lg^2 n)$ to $O(\lg n)$ for obliviously searching over $n$ items. We then present an oblivious heap protocol with rounds reduced from $O(\lg n)$ to $O(\lg \lg n)$ for insertions, and bandwidth reduced from $O(\lg^2 n)$ to $O(\lg n)$ for extractions. Finally, we also present the first oblivious AVL tree protocol for MPC where no party learns the data or the structure of the AVL tree, and can support arbitrary insertions and deletions with $O(\lg n)$ rounds and bandwidth. We experimentally evaluate our protocols with realistic network settings for a wide range of memory sizes to demonstrate their efficiency. For instance, we observe our binary search protocol provides $>27\times$ and $>3\times$ improvements in wall-clock time and bandwidth respectively over other approaches for a memory with $2^{26}$ items; for the same setting our heap's extract-min protocol achieves $>31\times$ speedup in wall-clock time and $>13\times$ reduction in bandwidth.

Anonymous credential schemes enable service providers to verify information that a credential holder willingly discloses, without needing any further personal data to corroborate that information, and without allowing the user to be tracked from one interaction to the next. Mercurial signatures are a novel class of anonymous credentials which show good promise as a simple and efficient construction without heavy reliance on zero-knowledge proofs. However, they still require significant development in order to achieve the functionality that most existing anonymous credential schemes provide. Encoding multiple attributes of the credential holder in such a way that they can be disclosed selectively with each use of the credential is often seen as a vital feature of anonymous credentials, and is one that mercurial signatures have not yet implemented. In this paper, we show a simple way to encode attributes in a mercurial signature credential and to regulate which attributes a credential holder can issue when delegating their credential to another user. We also extend the security model associated with mercurial signatures to account for the inclusion of attributes, and prove the security of our extension with respect to the original mercurial signature construction.

Filter permutators are a family of stream cipher designs that are aimed for hybrid homomorphic encryption. While originally operating on bits, they have been generalized to groups at Asiacrypt 2022, and instantiated for evaluation with the TFHE scheme which favors a filter based on (negacyclic) Look Up Tables (LUTs). A recent work of Gilbert et al., to appear at Asiacrypt 2023, exhibited (algebraic) weaknesses in the Elisabeth-4 instance, exploiting the combination of the 4-bit negacyclic LUTs it uses as filter. In this article, we explore the landscape of patches that can be used to restore the security of such designs while maintaining their good properties for hybrid homomorphic encryption. Starting with minimum changes, we observe that just updating the filter function (still with small negacyclic LUTs) is conceptually feasible, and propose the resulting Elisabeth-b4 design with three levels of NLUTs. We then show that a group permutator combining two different functions in the filter can simplify the analysis and improve performances. We specify the Gabriel instance to illustrate this claim. We finally propose to modify the group filter permutator paradigm into a mixed filter permutator, which considers the permutation of the key with elements in a group and a filter outputting elements in a different group. We specify the Margrethe instance as a first example of mixed filter permutator, with key elements in $\mathbb{F}_2$ and output in $\mathbb{Z}_{16}$, that we believe well-suited for recent fully homomorphic encryption schemes that can efficiently evaluate larger (not negacyclic) LUTs.

A recent line of research has introduced a systematic approach to explore the complexity of explicit construction problems through the use of meta problems, namely, the range avoidance problem (abbrev. $\textsf{Avoid}$) and the remote point problem (abbrev. $\textsf{RPP}$). The upper and lower bounds for these meta problems provide a unified perspective on the complexity of specific explicit construction problems that were previously studied independently. An interesting question largely unaddressed by previous works is whether $\textsf{Avoid}$ and $\textsf{RPP}$ are hard for simple circuits such as low-depth circuits.

In this paper, we demonstrate, under plausible cryptographic assumptions, that both the range avoidance problem and the remote point problem cannot be efficiently solved by nondeterministic search algorithms, even when the input circuits are as simple as constant-depth circuits. This extends a hardness result established by Ilango, Li, and Williams (STOC '23) against deterministic algorithms employing witness encryption for $\textsf{NP}$, where the inputs to $\textsf{Avoid}$ are general Boolean circuits.

Our primary technical contribution is a novel construction of witness encryption inspired by public-key encryption for certain promise language in $\textsf{NP}$ that is unlikely to be $\textsf{NP}$-complete. We introduce a generic approach to transform a public-key encryption scheme with particular properties into a witness encryption scheme for a promise language related to the initial public-key encryption scheme. Based on this translation and variants of standard lattice-based or coding-based PKE schemes, we obtain, under plausible assumption, a provably secure witness encryption scheme for some promise language in $\textsf{NP}\setminus \textsf{coNP}_{/\textsf{poly}}$. Additionally, we show that our constructions of witness encryption are plausibly secure against nondeterministic adversaries under a generalized notion of security in the spirit of Rudich's super-bits (RANDOM '97), which is crucial for demonstrating the hardness of $\textsf{Avoid}$ and $\textsf{RPP}$ against nondeterministic algorithms.

The advent of transformers has brought about significant advancements in traditional machine learning tasks. However, their pervasive deployment has raised concerns about the potential leakage of sensitive information during inference. Existing approaches using secure multiparty computation (MPC) face limitations when applied to transformers due to the extensive model size and resource-intensive matrix-matrix multiplications. In this paper, we present BOLT, a privacy-preserving inference framework for transformer models that supports efficient matrix multiplications and nonlinear computations. Combined with our novel machine learning optimizations, BOLT reduces the communication cost by 10.91x. Our evaluation on diverse datasets demonstrates that BOLT maintains comparable accuracy to floating-point models and achieves 4.8-9.5x faster inference across various network settings compared to the state-of-the-art system.

The literature gives the impression that (1) existing heuristics accurately predict how effective lattice attacks are, (2) non-ternary lattice systems are not vulnerable to hybrid multi-decoding primal attacks, and (3) the asymptotic exponents of attacks against non-ternary systems have stabilized.

This paper shows that 1 contradicts 2 and that 1 contradicts 3: the existing heuristics imply that hybrid primal key-recovery attacks are exponentially faster than standard non-hybrid primal key-recovery attacks against the LPR PKE with any constant error width. This is the first report since 2015 of an exponential speedup in heuristic non-quantum primal attacks against non-ternary LPR.

Quantitatively, for dimension n, modulus n^{Q_0+o(1)}, and error width w, a surprisingly simple hybrid attack reduces heuristic costs from 2^{(ρ+o(1))n} to 2^{(ρ-ρ H_0+o(1))n}, where z_0=2Q_0/(Q_0+1/2)^2, ρ=z_0 log_4(3/2), and H_0=1/(1+(lg w)/0.057981z_0). This raises the questions of (1) what heuristic exponent is achieved by more sophisticated hybrid attacks and (2) what impact hybrid attacks have upon concrete cryptosystems whose security analyses have ignored hybrid attacks, such as Kyber-512.

During the standardisation process of post-quantum cryptography, NIST encourages research on side-channel analysis for candidate schemes. As the recommended lattice signature scheme, CRYSTALS-Dilithium, when implemented on hardware, has only been subjected to the side-channel attack presented by Steffen et al. in IACR ePrint 2022. This attack is not complete and requires excessive traces. Therefore, we investigate the leakage of an FPGA (Kintex7) implementation of CRYSTALS-Dilithium using the CPA method, where with a minimum of 70000 traces partial private key coefficients can be recovered. As far as we know, this is the first work that applies power leakage to sidechannel attacks on FPGA implementations of CRYSTALS-Dilithium. Furthermore, we optimise the attack by extracting Point-of-Interests using known information due to parallelism (named CPA-PoI) and by iteratively utilising parallel leakages (named CPA-ITR). We experimentally demonstrate that when recovering the same number of key coefficients, the CPA-PoI and CPA-ITR reduce the number of traces used by up to 16.67 percent and 25 percent, respectively, compared to the CPA method. When attacking with the same number of traces, the CPA-PoI method and the CPA-ITR method increase the number of recovered key coefficients by up to 55.17 percent and 93.10 percent, respectively, compared to the CPA method. Our experiments confirm that the FPGA implementation of CRYSTALS-Dilithium is also very vulnerable to side-channel analysis.

Privacy-preserving machine learning (PPML) techniques have gained significant popularity in the past years. Those protocols have been widely adopted in many real-world security-sensitive machine learning scenarios, e.g., medical care and finance. In this work, we introduce $\mathsf{Aegis}$~-- a high-performance PPML platform built on top of a maliciously secure 3-PC framework over ring $\mathbb{Z}_{2^\ell}$. In particular, we propose a novel 2-round secure comparison (a.k.a., sign bit extraction) protocol in the preprocessing model. The communication of its semi-honest version is only 25% of the state-of-the-art (SOTA) constant-round semi-honest comparison protocol by Zhou et al.(S&P 2023); both communication and round complexity of its malicious version are approximately 50% of the SOTA (BLAZE) by Patra and Suresh (NDSS 2020), for $\ell=64$. Moreover, the communication of our maliciously secure inner product protocol is merely $3\ell$ bits, reducing 50% from the SOTA (Swift) by Koti et al. (USENIX 2021). Finally, the resulting ReLU and MaxPool PPML protocols outperform the SOTA by $4\times$ in the semi-honest setting and $10\times$ in the malicious setting, respectively.

Hiding countermeasures are the most widely utilized techniques for thwarting side-channel attacks, and their significance has been further emphasized with the advent of Post Quantum Cryptography (PQC) algorithms, owing to the extensive use of vector operations. Commonly, the Fisher-Yates algorithm is adopted in hiding countermeasures with permuted operation for its security and efficiency in implementation, yet the inherently sequential nature of the algorithm imposes limitations on hardware acceleration. In this work, we propose a novel method named Addition Round Rotation ARR, which can introduce a time-area trade-off with block-based permutation. Our findings indicate that this approach can achieve a permutation complexity level commensurate with or exceeding $2^{128}$ in a single clock cycle while maintaining substantial resistance against second-order analysis. To substantiate the security of our proposed method, we introduce a new validation technique --Identity Verification. This technique allows theoretical validation of the proposed algorithm's security and is consistent with the experimental results. Finally, we introduce an actual hardware design and provide the implementation results on Application-Specific Integrated Circuit (ASIC). The measured performance demonstrates that our proposal fully supports the practical applicability.

Recent advances in SNARK recursion and incrementally-verifiable computation are vast, but most of the efforts seem to be focused on a particular design goal - proving the result of a large computation known completely in advance.

There are other possible applications, requiring different design tradeoffs. Particularly interesting direction is a case with a swarm of collaborating provers, communicating over a peer-to-peer network - which requires to also optimize the amount of data exchanged between the participants of the swarm.

One notable such application is Ethereum's consensus, which requires to aggregate millions of signatures of individual validators.

In this technical note, we propose an informal notion of an end-to-end IVC scheme, which means that the amount of data that the prover needs exchange with the previous prover to continue the computation is small.

We explore the existing design space from this point of view, and suggest an approach to constructing such a scheme by combining the PlonK proof systemwith the recent Cyclefold construction.

A randomness beacon is a source of continuous and publicly verifiable randomness which is of crucial importance for many applications. Existing works on distributed randomness beacons suffer from at least one of the following drawbacks: (i) security only against a static/non-adaptive adversary, (ii) each epoch takes many rounds of communication, or (iii) computationally expensive tools such as Proof-of-Work (PoW) or Verifiable Delay Functions (VDF). In this paper, we introduce $\mathsf{GRandLine}$, the first adaptively secure randomness beacon protocol that overcomes all these limitations while preserving simplicity and optimal resilience in the synchronous network setting. We achieve our result in two steps. First, we design a novel distributed key generation (DKG) protocol $\mathsf{GRand}$ that runs in $\mathcal{O}(\lambda n^2\log{n})$ bits of communication but, unlike most conventional DKG protocols, outputs both secret and public keys as group elements. Second, following termination of $\mathsf{GRand}$, parties can use their keys to derive a sequence of randomness beacon values, where each random value costs only a single asynchronous round and $\mathcal{O}(\lambda n^2)$ bits of communication. We implement $\mathsf{GRandLine}$ and evaluate it using a network of up to 64 parties running in geographically distributed AWS instances. Our evaluation shows that $\mathsf{GRandLine}$ can produce about 2 beacon outputs per second in a network of 64 parties. We compare our protocol to the state-of-the-art randomness beacon protocols in the same setting and observe that it vastly outperforms them.

This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata Skipping Alternating Finite Automata (SAFA) that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).

Falcon is one out of three post-quantum signature schemes which have been selected for standardization by NIST in July 2022. To the best of our knowledge, Falcon is the only selected algorithm that does not yet have a publicly reported hardware description that performs signing or key generation. The reason might be that the Falcon signature and key generation algorithms do not fit well in hardware due to the use of floating-point numbers and recursive functions. This publication describes the first hardware implementation for Falcon signing and key generation. To overcome the complexity of the Falcon algorithms, High-Level Synthesis (HLS) was preferred over a hardware description language like Verilog or VHDL. Our HLS code is based on the C reference implementation available at NIST. We describe the required modifications in order to be compliant with HLS, such as rewriting recursive functions into iterative versions. The hardware core at security level 5 requires 45,223 LUTs, 41,370 FFs, 182 DSPs, and 37 BRAMs to calculate one signature in 8.7 ms on a Zynq UltraScale+ FPGA. Security level 5 key generation takes 320.3 ms and requires 100,649 LUTs, 91,029 FFs, 1,215 DSPs, and 69 BRAMs.

Multi-signatures allow to combine individual signatures from different signers on the same message into a short aggregated signature. Newer schemes further allow to aggregate the individual public keys, such that the combined signature gets verified against a short aggregated key. This makes them a versatile alternative to threshold or distributed signatures: the aggregated key can serve as group key, and signatures under that key can only be computed with the help of all signers. What makes multi-signatures even more attractive is their simple key management, as users can re-use the same secret key in several and ad-hoc formed groups. In that context, it will be desirable to not sacrifice privacy as soon as keys get re-used and ensure that users are not linkable across groups. In fact, when multi-signatures with key aggregation were proposed, it was claimed that aggregated keys hide the signers' identities or even the fact that it is a combined key at all. In our work, we show that none of the existing multi-signature schemes provide these privacy guarantees when keys get re-used in multiple groups. This is due to the fact that all known schemes deploy deterministic key aggregation. To overcome this limitation, we propose a new variant of multi-signatures with probabilistic yet verifiable key aggregation. We formally define the desirable privacy and unforgeability properties in the presence of key re-use. This also requires to adapt the unforgeability model to the group setting, and ensure that key-reuse does not weaken the expected guarantees. We present a simple BLS-based scheme that securely realizes our strong privacy and security guarantees. We also formalize and investigate the privacy that is possible by deterministic schemes, and prove that existing schemes provide the advertised privacy features as long as one public key remains secret.

Encrypted search schemes have been proposed to address growing privacy concerns. However, several leakage-abuse attacks have highlighted the shortcomings of these schemes. The literature remains vague about the consequences of these attacks for real-world applications: are these attacks dangerous in practice? Is it safe to use these schemes? Do we even need countermeasures?

This paper introduces a novel mathematical model for attackers' knowledge using statistical estimators. Our model reveals that any attacker's knowledge is inherently noisy, which limits attack effectiveness. This inherent noise can be considered a security guarantee, a natural attack mitigation. Capitalizing on this insight, we develop a risk assessment protocol to guide real-world deployments. Our findings demonstrate that limiting the index size is an efficient leverage to bound attack accuracy. Finally, we employ similar statistical methods to enhance attack analysis methodology. Hence, our work offers a fresh perspective on SSE attacks and provides practitioners and researchers with novel methodological tools.