IACR News
Here you can see all recent updates to the IACR webpage. These updates are also available:
04 February 2022
Valletta, Malta, 25 April - 29 April 2022
Submission deadline: 18 February 2022
Notification: 4 March 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.
01 February 2022
University College Cork, Ireland
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/
The University of Manchester, Department of Computer Science, Manchester, UK
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
SupraOracles
Closing date for applications:
Contact: Lee
More information: https://boards.greenhouse.io/supraoracles/jobs/4278334004
31 January 2022
Kosei Sakamoto, Fukang Liu, Yuto Nakano, Shinsaku Kiyomoto, Takanori Isobe
Zilin Liu, Anjia Yang, Jian Weng, Tao Li, Huang Zeng, Xiaojian Liang
Ziaur Rahman, Xun Yi, Ibrahim Khalil
Theodore Bugnet, Alexei Zamyatin
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.
Amin Abdulrahman, Vincent Hwang, Matthias J. Kannwischer, Daan Sprenkels
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.
Christina Boura, Rachelle Heim Boissier, Yann Rotella
Jan-Pieter D'Anvers, Michiel Van Beirendonck, Ingrid Verbauwhede
Ananya Appan, Anirudh Chandramouli, Ashish Choudhury
Rohon Kundu, Alessandro de Piccoli, Andrea Visconti
Aydin Abadi, Steven J. Murdoch
Soundes Marzougui, Vincent Ulitzsch, Mehdi Tibouchi, Jean-Pierre Seifert
Varun Madathil, Alessandra Scafuro, Kemafor Anyanwu, Sen Qiao, Akash Pateria, Binil Starly
Matthias Fitzi, Xuechao Wang, Sreeram Kannan, Aggelos Kiayias, Nikos Leonardos, Pramod Viswanath, Gerui Wang
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.