IACR News
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26 January 2024
Ibrahim Yakut, Huseyin Polat
Emanuele Bellini, Alessandro De Piccoli, Mattia Formenti, David Gerault, Paul Huynh, Simone Pelizzola, Sergio Polese, Andrea Visconti
Bo Jiang, Jian Du, Qiang Yan
Daniel Nager
Sanjam Garg, Mohammad Hajiabadi, Peihan Miao, Alice Murphy
In this work, we push the limits further and achieve laconic branching programs from the Diffie-Hellman assumption. In particular, the receiver holds a large branching program $P$ and the sender holds a short input $x$. We present a two-round 2PC protocol that allows the receiver to learn $x$ iff $P(x) =1$, and nothing else. The communication only grows with the size of $x$ and the depth of $P$, and does not further depend on the size of $P$.
Albert Yu, Hai H. Nguyen, Aniket Kate, Hemanta K. Maji
- We present a key agreement protocol with a novel combinatorial insight to offer a 200% throughput over the (FOCS–2006) study; i.e., using the same number of messages, we can (almost) double the bit-length of the agreed key. We also prove the near optimality of our approach.
- We offer unconditionally secure protocols for the (random) string oblivious transfer functionalities. We present a $1$-round chosen message random string oblivious transfer and show how to extend it to a non-interactive (random) string oblivious transfer protocol and a $2$-round chosen message string oblivious transfer.
- We prove a $1$-round lower bound for BEC under certain conditions.
Central to our technical contributions is the abstraction of a distributional variant of the random ABB functionality. Investigating the concrete efficiency of founding MPC from this primitive leads to fascinating new mathematical challenges in well-established MPC models, which will be of broader interest to the community.
Luke Demarest, Sohaib Ahmad, Sixia Chen, Benjamin Fuller, Alexander Russell
This is particularly frustrating given the long line of research that has developed theoretical tools---known as fuzzy extractors---that enable secure, privacy preserving biometric authentication with public enrollment data. Unfortunately, the best known constructions involving these rigorous tools can only provide substantial true accept rates with an estimated security of $32$ bits for the iris (Simhadri et al., ISC 2019) and 45 bits for the face (Zhang, Cui, and Yu, ePrint 2021/1559).
This work introduces FiveEyes, an iris key derivation system that integrates an improved feature extractor with a fuzzy extractor that leverages a new mechanism, which we formally analyze, for selecting verification subsets based on statistics of the iris. (These statistics are computed from a class disjoint dataset from our test set.) We present various parameter regimes in order to highlight different true accept rates: 1. $65$ bits of security (equivalent to $87$ bits with a password) at $12\%$ true accept rate, and 2. $50$ bits of security (equivalent to $72$ bits with a password) at $45\%$ true accept rate. We remark that powerful techniques are known that amplify true accept rates (Davida et al., IEEE S&P 1998); in particular, for the first time these results indicate practical viability of biometric authentication with strongcryptographic security.
Alberto Garoffolo, Dmytro Kaidalov, Roman Oliynykov
Further efficiency improvement to avoid this bottleneck lies in utilizing distributed recursive proof composition to aggregate multiple existing proofs into one that verifies all underlying proofs.
Building upon this concept, we present a new protocol for decentralized recursive proof aggregation allowing one unique proof to aggregate many input proofs to be efficiently verified on-chain, increasing the throughput and cost efficiency of SNARK-based blockchains. The protocol is designed for decentralized environments where independent actors (provers) can join and contribute to the proof generation process. We also present an incentive scheme for such actors. The protocol is abstract enough to be used with a variety of proving systems that support recursive aggregation.
25 January 2024
Jaipur, India, 16 December - 20 December 2024
Submission deadline: 10 July 2024
Notification: 10 September 2024
TU Wien Informatics, Vienna, Austria
Closing date for applications:
Contact: Zeta Avarikioti and Mattero Maffei
More information: https://tools.spycode.at/recruiting/call/4
University of California San Diego, Department of Electrical and Computer Engineering; San Diego, CA
Requirements:
- Ph.D. in Computer Engineering, Computer Science, or a closely related field
- Strong ability in at least C/C++ or Rust
- Familiarity with popular open-source zero-knowledge proof frameworks
- Publication record in top venues, with proven research record around zero-knowledge proofs
- Strong theoretical understanding of zero-knowledge proofs and its various constructions
- Ability to work on-site in San Diego
Closing date for applications:
Contact: Farinaz Koushanfar (fkoushanfar@ucsd.edu)
University of California San Diego, Department of Electrical and Computer Engineering; San Diego, CA
Requirements:
- Ph.D. in Computer Science, Computer Engineering, or a closely related field
- Strong ability in at least C/C++, Python, or Rust
- Familiarity with popular open-source privacy-preserving computation frameworks
- Publication record in top venues, with proven research record in applied cryptography or adjacent field
- Strong applied cryptography skills
- Ability to work on-site in San Diego
To apply, please send your CV to Farinaz Koushanfar at the email: fkoushanfar@ucsd.edu
Closing date for applications:
Contact: Farinaz Koushanfar (fkoushanfar@ucsd.edu)
Technology Innovation Institute
Closing date for applications:
Contact: mohammed.hannan@tii.ae
Technology Innovation Institute
Closing date for applications:
Contact: mohammed.hannan@tii.ae
University of Bern, Switzerland
A Ph.D. position is available in the Cryptology and Data Security research group at the Institute of Computer Science, University of Bern, led by Christian Cachin.
Our research addresses all aspects of security in distributed systems, especially cryptographic protocols, consistency, consensus, and cloud-computing security. We are particularly interested in blockchains, distributed ledger technology, cryptocurrencies, and their security and economics. To learn more about our research topics, please explore https://crypto.unibe.ch. We are part of IC3: The Initiative for Cryptocurrencies and Contracts (http://www.initc3.org>).
Candidates should have a strong background in computer science and its mathematical foundations. They should like conceptual, rigorous thinking for working theoretically. Demonstrated expertise in cryptography, distributed computing, or blockchain technology is a plus. Applicants must hold a master degree in the relevant research fields.
Positions are available for starting in Spring 2024 and come with a competitive salary. The selection process runs until suitable candidates have been found. The University of Bern conducts excellent research and lives up its vision that "Knowledge generates value". The city of Bern lies in the center of Switzerland and offers some of the highest quality of life worldwide.
If you are interested, please apply be sending email with **one single PDF file** and **subject line** set to **Application for Ph.D.**, addressed directly to Prof. Christian Cachin at **crypto.inf (at) unibe.ch.**.
Since we receive many applications, we encourage you to include material that explains your interests, demonstrates your strengths, and sets you apart from others.
Closing date for applications:
Contact: Christian Cachin, https://crypto.unibe.ch/cc/
More information: https://crypto.unibe.ch/jobs/
22 January 2024
Pierrick Méaux, Dibyendu Roy
Dung Bui, Kelong Cong, Cyprien Delpech de Saint Guilhem
A more efficient technique for constructing GGM trees is the half-tree technique, introduced by Guo et al. (Eurocrypt 2023). Our work builds an all-but-one vector commitment scheme from the half-tree technique, and further generalizes it to an all-but-\(\tau\) vector commitment scheme. Crucially, our work avoids the use of the random oracle assumption in an important step, which means our binding proof is non-trivial and instead relies on the random permutation oracle. Since this oracle can be instantiated using fixed-key AES which has hardware support, we achieve faster signing and verification times.
We integrate our vector commitment scheme into FAEST (faest.info), a round one candidate in the NIST standardization process, and demonstrates its performance with a prototype implementation. For \(\lambda = 128\), our experimental results show a nearly \(3.5\)-fold improvement in signing and verification times.
Yasuhiko Ikematsu, Rika Akiyama
Tian Zhou, Fangyu Zheng, Guang Fan, Lipeng Wan, Wenxu Tang, Yixuan Song, Yi Bian, Jingqiang Lin
In this paper, we present a comprehensive exploration of NVIDIA Tensor Cores and introduce a novel framework tailored specifically for Kyber. Firstly, we propose two innovative approaches that efficiently break down Kyber's NTT into iterative matrix multiplications, resulting in approximately a 75% reduction in costs compared to the state-of-the-art scanning-based methods.Secondly, by reversing the internal mechanisms, we precisely manipulate the internal resources of Tensor Cores using assembly-level code instead of inefficient standard interfaces, eliminating memory accesses and redundant function calls. Finally, building upon our highly optimized NTT, we provide a complete implementation for all parameter sets of Kyber. Our implementation surpasses the state-of-the-art Tensor Core based work, achieving remarkable speed-ups of 1.93x, 1.65x, 1.22x and 3.55x for polyvec_ntt, KeyGen, Enc and Dec in Kyber-1024, respectively. Even when considering execution latency, our throughput-oriented full Kyber implementation maintains an acceptable execution latency. For instance, the execution latency ranges from 1.02 to 5.68 milliseconds for Kyber-1024 on R3080 when achieving the peak throughput.