International Association
for Cryptologic Research

Event date: 25 April to 29 April 2022
Submission deadline: 18 February 2022
Notification: 4 March 2022

PKC 2022 will be held virtually on March 8-11, 2022.

The registration for PKC 2022 is now open: https://pkc.iacr.org/2022/registration.php

Registration is free for IACR members; non-IACR members will be asked to pay the IACR membership fee during registration.

The School of Computer Science & Information Technology (CSIT) seeks to appoint a lecturer (assistant professor) in Computer Science (Cybersecurity) to complement and strengthen the Schools’ research and teaching interests. Computer security has been a topic of research and teaching in the School for over thirty years. The school continues to grow with the appointment of new staff with cyber security expertise, introduction of new courses, and significant development of our cybersecurity research portfolio.

The school strategy is to expand its research and teaching in the area of Cybersecurity and candidates with such expertise are encouraged to apply. The School seeks to appoint a committed computer science academic, a dynamic and thoughtful individual who will contribute to its research-led teaching ethos and research agenda.

The School of CSIT has 32 full-time academic staff and offers degrees at bachelors, masters and doctoral level. It offers a welcoming and open working environment, with excellent administrative and technical support, and an inclusive collegiate experience. Academic staff in the school have leadership roles in major national and international research initiatives, including the SFI funded research centers CONNECT (Centre for Future Networks and Communications), CONFIRM (Centre for Smart Manufacturing), Insight (Centre for Data Analytics), LERO (Irish Software Research Centre), and the SFI research spokes BAV (Blended Autonomous Vehicles) and ENABLE (Smart Communities). In addition, school academics lead and host the SFI Centre for Research Training in Advanced Networks for Sustainable Societies and the SFI Centre for Research Training in Artificial Intelligence. The Cork area is home to a cybersecurity cluster of about 25 companies, including multinationals that are well-known for their security products and services, many of whom the School engages with for student internships, research sponsorship and collaboration.

Candidates should apply before 12 noon (Irish Local Time) on Tuesday, 22nd February 2022

Closing date for applications:

Contact: Informal enquiries can be made, in confidence, to the Head of School, Professor Utz Roedig: u.roedig@ucc.ie

Applications must be submitted online via the University College Cork vacancy portal: https://ore.ucc.ie/

More information: https://www.ucc.ie/en/compsci/vacancies/

We are looking for a research associate to join an ambitious project (EnnCore - https://enncore.github.io/) in the space of Secure and Privacy-preserving AI Models.

You will enjoy designing, developing and evaluating novel AI models (deep neural networks) that are privacy-preserving and robust against attacks. The project will involve the continuous interaction with experts in explainable AI and formal software verification. You will also have the opportunity to build, use cases and to collaborate with domain experts in areas such as cancer research and energy trading. You will design, develop and evaluate new models in the context of their accuracy, privacy-protection and robustness. This position may include research on a diverse set of techniques such as federated learning, homomorphic encryption, multiparty computation and adversarial methods.

The post is initially for one year, with the possibility for extensions. Interviews are anticipated to take place a week after the closing date.

You should have a PhD in Computer Science or a closely related field together with a track record of international publications in applied machine learning or secure computation. Examples of fields of interests are:

• Federated Learning
• Homomorphic Encryption
• Secure Multiparty Computation
• Differential Privacy
• Safety Mechanisms in AI Systems
• Adversarial Methods

Closing date for applications:

Contact: Mustafa A. Mustafa: mustafa.mustafa[at]manchester.ac.uk

More information: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=21631

We are looking for an Applied Researcher to enhance our research works at SupraOracles. The team is actively researching and developing in the core areas of fault tolerant distributed systems, formal verification, program analysis, interoperable blockchains, and cryptography and applying them in pushing the limits of blockchain technology in terms of scalability and reliability. An ideal candidate brings in his / her expertise from the domains of mathematics, cryptography, formal methods, probability theory to rigorously analyse, reason and solve the challenging problems. This exciting work involves interacting with researchers, building prototypes, experimenting, articulating, designing algorithms and implementing them. We thrive on trust and honesty. We believe in the positive and ethical impacts these cutting-edge technologies in a decentralized environment can make on the world. Your alignment and cultural fitment to these core values and beliefs are of considerable value to us. Responsibilities Studying, comprehending and discussing research papers Theoretical / mathematical and empirical evaluation of the research ideas Implementing prototypes and / or production ready software Lucid and articulate communication via discussions, reports / presentations / papers Are you the right person for this role? The ideal candidate for us has: Masters or PhD in computer science Published papers at top tier peer-reviewed venues in any of the fields of cryptography, distributed systems design, formal methods, algorithms Experience working in a research lab Good familiarity in a couple of programming languages in the list of Java, Rust, GoLang, JavaScript/NodeJS, Solidity (this mainly depends upon the project) Experience in working with GitHub codebases Hands-on experience on open source projects Standard algorithms and data structure knowledge Basic understanding of cryptography and smart contract development Pro-active communication and collaboration abilities with native-level proficiency in written and oral English Preferred: Mathematics background with strong hold on probability modelling and analysis.

Closing date for applications:

Contact: Lee

More information: https://boards.greenhouse.io/supraoracles/jobs/4278334004

In this paper, we present an AES-based authenticated-encryption with associated-data scheme called Rocca, with the purpose to reach the requirements on the speed and security in 6G systems. To achieve ultrafast software implementations, the basic design strategy is to take full advantage of the AES-NI and SIMD instructions as that of the AEGIS family and Tiaoxin-346. Although Jean and Nikolić have generalized the way to construct efficient round functions using only one round of AES (aesenc) and 128-bit XOR operation and have found several efficient candidates, there still seems to exist potential to further improve it regarding speed and state size. In order to minimize the critical path of one round, we remove the case of applying both aesenc and XOR in a cascade way for one round. By introducing a cost-free block permutation in the round function, we are able to search for candidates in a larger space without sacrificing the performance. Consequently, we obtain more efficient constructions with a smaller state size than candidates by Jean and Nikolić. Based on the newly-discovered round function, we carefully design the corresponding AEAD scheme with 256-bit security by taking several reported attacks on the AEGIS family and Tiaxion-346 into account. Our AEAD scheme can reach 178 Gbps which is almost 5 times faster than the AEAD scheme of SNOW-V. Rocca is also much faster than other efficient schemes with 256-bit key length, e.g. AEGIS-256 and AES-256-GCM. As far as we know, Rocca is the first dedicated cryptographic algorithm targeting 6G systems, i.e., 256-bit key length and the speed of more than 100 Gbps.

Payment channel network (PCN), not only improving the transaction throughput of blockchain but also realizing cross-chain payment, is a very promising solution to blockchain scalability problem. Most existing PCN constructions focus on either atomicity or privacy properties. Moreover, they are built on specific scripting features of the underlying blockchain such as HTLC or are tailored to several signature algorithms like ECDSA and Schnorr. In this work, we devise a Generalized Multi-Hop Locks (GMHL) based on adaptor signature and randomizable puzzle, which supports both atomicity and privacy preserving(unlinkability). We instantiate GMHL with a concrete design that relies on a Guillou-Quisquater-based adaptor signature and a novel designed RSA-based randomizable puzzle. Furthermore, we present a generic PCN construction based on GMHL, and formally prove its security in the universal composability framework. This construction only requires the underlying blockchain to perform signature verification, and thus can be applied to various (non-/Turing-complete) blockchains. Finally, we simulate the proposed GMHL instance and compare with other protocols. The results show that our construction is efficient comparable to other constructions while remaining the good functionalities.

Industry 4.0 is all about doing things in a concurrent, secure, and fine-grained manner. IoT edge-sensors and their associated data play a predominant role in today's industry ecosystem. Breaching data or forging source devices after injecting advanced persistent threats (APT) damages the industry owners' money and loss of operators' lives. The existing challenges include APT injection attacks targeting vulnerable edge devices, insecure data transportation, trust inconsistencies among stakeholders, incompliant data storing mechanisms, etc. Edge-servers often suffer because of their lightweight computation capacity to stamp out unauthorized data or instructions, which in essence, makes them exposed to attackers. When attackers target edge servers while transporting data using traditional PKI-rendered trusts, consortium blockchain (CBC) offers proven techniques to transfer and maintain those sensitive data securely. With the recent improvement of edge machine learning, edge devices can filter malicious data at their end which largely motivates us to institute a Blockchain and AI aligned APT detection system. The unique contributions of the paper include efficient APT detection at the edge and transparent recording of the detection history in an immutable blockchain ledger. In line with that, the certificateless data transfer mechanism boost trust among collaborators and ensure an economical and sustainable mechanism after eliminating existing certificate authority. Finally, the edge-compliant storage technique facilitates efficient predictive maintenance. The respective experimental outcomes reveal that the proposed technique outperforms the other competing systems and models.

The need for cross-blockchain interoperability is higher than ever. Today, there exists a plethora of blockchain-based cryptocurrencies, with varying levels of adoption and diverse niche use cases, and yet communication across blockchains is still in its infancy. Despite the vast potential for novel applications in an interoperable ecosystem, cross-chain tools and protocols are few and often limited.

Cross-chain communication requires a trusted third party, as the Fair Exchange problem is reducible to it. However, the decentralised consensus of blockchains can be used as a source of trust, and financial incentives can achieve security. XCLAIM uses these principles to enable collateralised cryptocurrency-backed assets to be created and used. However, full collateralization is inefficient, and to protect against exchange rate fluctuations overcollateralization is necessary. This is a significant barrier to scaling, and as a result, in practice, most systems still employ a centralised architecture.

In this work, we introduce XCC, an extension to the XCLAIM framework which allows for a significant reduction in collateral required. By making use of periodic, timelocked commitments on the backing blockchain, XCC decouples locked collateral from issued CBAs, allowing fractional collateralization without loss of security. We instantiate XCC between Bitcoin and Ethereum to showcase practical feasibility. XCC is compatible with the majority of existing blockchains without modification.

This paper presents faster implementations of the lattice-based schemes Dilithium and Kyber on the Cortex-M4. Dilithium is one of the three signature finalists in the NIST post-quantum project (NIST PQC), while Kyber is one of the four key-encapsulation mechanism (KEM) finalists.

Our optimizations affect the core polynomial arithmetic using the number-theoretic transform (NTT) of both schemes. Our main contributions are threefold: We present a faster signed Barrett reduction for Kyber, propose to switch to a smaller prime modulus for the polynomial multiplications \(c\mathbf{s}_1\) and \(c\mathbf{s}_2\) in the signing procedure of Dilithium, and apply various known optimizations to the polynomial arithmetic in both schemes. Using a smaller prime modulus is particularly interesting as it allows using the Fermat number transform resulting in especially fast code.

We outperform the state-of-the-art for both Dilithium and Kyber. For Dilithium, our NTT and iNTT are faster by 5.2% and 5.7%. Switching to a smaller modulus results in speed-up of 33.1%-37.6% for the relevant operations (sum of basemul and iNTT) in the signing procedure. For Kyber, the optimizations results in 15.9%-17.8% faster matrix-vector product which presents the core arithmetic operation in Kyber.

Panther is a sponge-based lightweight authenticated encryption scheme published at Indocrypt 2021. Its round function is based on four Nonlinear Feedback Shift Registers (NFSRs). We show here that it is possible to fully recover the secret key of the construction by using a single known plaintext-ciphertext pair and with minimal computational ressources. Furthermore, we show that in a known ciphertext setting an attacker is able with the knowledge of a single ciphertext to decrypt all plaintext blocks expect for the very first ones and can forge the tag with only one call and probability one. As we demonstrate, the problem of the design comes mainly from the low number of iterations of the round function during the absorption phase. All of our attacks have been implemented and validated.

Masked comparison is one of the most expensive operations in side-channel secure implementations of lattice-based post-quantum cryptography, especially for higher masking orders. First, we introduce two new masked comparison algorithms, which improve the arithmetic comparison of D'Anvers et al. and the hybrid comparison method of Coron et al. respectively. We then look into implementation-specific optimizations, and show that small specific adaptations can have a significant impact on the overall performance. Finally, we implement various state-of-the-art comparison algorithms and benchmark them on the same platform (ARM-Cortex M4) to allow a fair comparison between them. We improve on the arithmetic comparison of D'Anvers et al. with a factor $\approx 20\%$ by using Galois Field multiplications and the hybrid comparison of Coron et al. with a factor $\approx 25\%$ by streamlining the design. Our implementation-specific improvements allow a speedup of a straightforward comparison implementation of $\approx 33\%$. We discuss the differences between the various algorithms and provide the implementations and a testing framework to ease future research.

Secure multi-party computation (MPC) is a fundamental problem in secure distributed computing. The optimal resilience for perfectly-secure MPC in synchronous and asynchronous networks is $t < n/3$ and $t < n/4$ respectively, where $n$ is the number of parties and $t$ is the number of corruptions. A natural question is whether there exists a protocol tolerating $t_s < n/3$ corruptions in a synchronous network and $t_a < n/4$ corruptions in an asynchronous network. We design such a protocol, if $3t_s + t_a < n$. For our protocol, we present a perfectly-secure Byzantine agreement (BA) protocol, tolerating $t < n/3$ corruptions in any network and a perfectly-secure verifiable secret-sharing (VSS) protocol, tolerating $t_s$ and $t_a$ corruptions in a $synchronous$ and an asynchronous network respectively.

NTRU is a lattice-based public-key cryptosystem that has been selected as one of the Round III finalists at the NIST Post-Quantum Cryptography Standardization. Compressing the key sizes to increase efficiency has been a long-standing open question for lattice-based cryptosystems. In this paper we provide a solution to three seemingly opposite demands for NTRU cryptosystem: compress the key size, increase the security level, optimize performance by implementing fast polynomial multiplications. We consider a specific variant of NTRU known as NTRU-NTT. To perform polynomial optimization, we make use of the Number-Theoretic Transformation (NTT) and hybridize it with the Karatsuba Algorithm. Previous work done in providing 2-part Hybridized NTT-Karatsuba Algorithm contained some operational errors in the product expression, which have been detected in this paper. Further, we conjectured the corrected expression and gave a detailed mathematical proof of correctness. In this paper, for the first time, we optimize NTRU-NTT using the corrected Hybridized NTT-Karatsuba Algorithm. The significance of compressing the value of the prime modulus $q$ lies with decreasing the key sizes. We achieve a 128-bit post-quantum security level for a modulus value of 83,969 which is smaller than the previously known modulus value of 1,061,093,377, while keeping $n$ constant at 2048.

An "Authorised Push Payment" (APP) fraud refers to the case where fraudsters deceive a victim to make payments to bank accounts controlled by them. The total amount of money stolen via APP frauds is swiftly growing. Although regulators have provided guidelines to improve victims' protection, the guidelines are vague and the victims are not receiving sufficient protection. To facilitate victims' reimbursement, in this work, we propose a protocol called "Payment with Dispute Resolution" (PwDR) and formally define it. The protocol lets an honest victim prove its innocence to a third-party dispute resolver while preserving the protocol participants' privacy. It makes black-box use of a standard online banking system. We evaluate its asymptotic cost and runtime via a prototype implementation. Our evaluation indicates that the protocol is efficient. It imposes only O(1) overheads to the customer and bank. Also, it takes a dispute resolver 0.09 milliseconds to settle a dispute between the two parties.

We present an end-to-end (equivalent) key recovery attack on the Dilithium lattice-based signature scheme, one of the top contenders in the NIST postquantum cryptography competition. The attack is based on a small side-channel leakage we identified in a bit unpacking procedure inside Dilithium signature generation. We then combine machine-learning based profiling with various algorithmic techniques, including least squares regression and integer linear programming, in order to leverage this small leakage into essentially full key recovery: we manage to recover, from a moderate number of side-channel traces, enough information to sign arbitrary messages. We confirm the practicality of our technique using concrete experiments against the ARM Cortext-M4 implementation of Dilithium, and verify that our attack is robust to real-world conditions such as noisy power measurements. This attack appears difficult to protect against reliably without strong side-channel countermeasures such as masking of the entire signing algorithm, and underscores the necessity of implementing such countermeasures despite their known high cost.

Technology is being used increasingly for lowering the trust barrier in domains where collaboration and cooperation are necessary, but reliability and efficiency are critical due to high stakes. An example is an industrial marketplace where many suppliers must participate in production while ensuring reliable outcomes; hence, partnerships must be pursued with care. Online marketplaces like Xometry facilitate partnership formation by vetting suppliers and mediating the marketplace. However, such an approach requires that all trust be vested in the middleman. This centralizes control, making the system vulnerable to being biased towards specific providers. The use of blockchains is now being explored to bridge the trust gap needed to support decentralizing marketplaces, allowing suppliers and customers to interact more directly by using the information on the blockchain. A typical scenario is the need to preserve privacy in certain interactions initiated by the buyer (e.g., protecting a buyer’s intellectual property during outsourcing negotiations). In this work, we initiate the formal study of matching between suppliers and buyers when buyer-privacy is required for some marketplace interactions and make the following contributions. First, we devise a formal security definition for private interactive matching in the Universally Composable (UC) Model that captures the privacy and correctness properties expected in specific supply chain marketplace interactions. Second, we provide a lean protocol based on any programmable blockchain, anonymous group signatures, and public-key encryption. Finally, we implement the protocol by instantiating some of the blockchain logic by extending the BigChainDB blockchain platform.

Resource-based consensus is the backbone of permissionless distributed ledger systems. The security of such protocols relies fundamentally on the level of resources actively engaged in the system. The variety of different resources (and related proof protocols, some times referred to as PoX in the literature) raises the fundamental question whether it is possible to utilize many of them in tandem and build multi-resource consensus protocols. The challenge in combining different resources is to achieve fungibility between them, in the sense that security would hold as long as the cumulative adversarial power across all resources is bounded.

In this work, we put forth Minotaur, a multi-resource blockchain consensus protocol that combines proof of work (PoW) and proof-of-stake (PoS), and we prove it optimally fungible. At the core of our design, Minotaur operates in epochs while continuously sampling the active computational power to provide a fair exchange between the two resources, work and stake. Further, we demonstrate the ability of Minotaur to handle a higher degree of work fluctuation as compared to the Bitcoin blockchain; we also generalize Minotaur to any number of resources.

We demonstrate the simplicity of Minotaur via implementing a full stack client in Rust (available open source). We use the client to test the robustness of Minotaur to variable mining power and combined work/stake attacks and demonstrate concrete empirical evidence towards the suitability of Minotaur to serve as the consensus layer of a real-world blockchain.

The transition from paper-based information to Electronic Health Records (EHRs) has driven various advancements in the modern healthcare industry. In many cases, patients need to share their EHR with healthcare professionals. Given the sensitive and security-critical nature of EHRs, it is essential to consider the security and privacy issues of storing and sharing EHR. However, existing security solutions are excessively encrypting the whole database, where for each access request the entire database is required to be decrypted, which is a time-consuming process. On the other hand, the use of EHR for medical research (e.g. development of precision medicine, diagnostics techniques etc.) as well optimisation of practises in healthcare organisations, requires the EHR to be analysed and for that they should be easily accessible without compromising the privacy of the patient. In this paper, we propose an efficient technique called E-Tenon that not only securely keeps all EHR publicly accessible but also provides the desirable security features. To the best of our knowledge, this is the first work in which an Open Database is used for protecting EHR. The proposed concept of E-Tenon empowers patients to securely share their EHR under multi-level, fine-grained access policies defined by themselves. Analyses show that our system outperforms existing solutions in terms of computational complexity.

We address the problem of efficiently verifying a commitment in a two-party computation. This addresses the scenario where a party P1 commits to a value x to be used in a subsequent secure computation with another party P2 that wants to receive assurance that P1 did not cheat, i.e. that x was indeed the value inputted into the secure computation. Our constructions operate in the publicly verifiable covert (PVC) security model, which is a relaxation of the malicious model of MPC appropriate in settings where P1 faces a reputational harm if caught cheating. We introduce the notion of PVC commitment scheme and indexed hash functions to build commitments schemes tailored to the PVC framework, and propose constructions for both arithmetic and Boolean circuits that result in very efficient circuits. From a practical standpoint, our constructions for Boolean circuits are 60× faster to evaluate securely, and use 36× less communication than baseline methods based on hashing. Moreover, we show that our constructions are tight in terms of required non-linear operations, by proving lower bounds on the nonlinear gate count of commitment verification circuits. Finally, we present a technique to amplify the security properties our constructions that allows to efficiently recover malicious guarantees with statistical security.