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21 September 2020
Mark Abspoel, Daniel Escudero, Nikolaj Volgushev
Our starting point is to apply an existing generic MPC protocol to a standard decision tree learning algorithm, which we then optimize in several ways. We exploit the fact that even if we allow the data to have continuous values, which a priori might require fixed or floating point representations, the output of the tree learning algorithm only depends on the relative ordering of the data. By obliviously sorting the data we reduce the number of comparisons needed per node to $O(N \log^2 N)$ from the naive $O(N^2)$, where $N$ is the number of training records in the dataset, thus making the algorithm feasible for larger datasets. This does however introduce a problem when duplicate values occur in the dataset, but we manage to overcome this problem with a relatively cheap subprotocol. We show a procedure to convert a sorting network into a permutation network of smaller complexity, resulting in a round complexity of $O(\log N)$ per layer in the tree.
We implement our algorithm in the MP-SPDZ framework and benchmark our implementation for both passive and active three-party computation using arithmetic modulo $2^{64}$. We apply our implementation to a large scale medical dataset of $\approx 290\,000$ rows using random forests, and thus demonstrate practical feasibility of using MPC for privacy-preserving machine learning based on decision trees for large datasets.
Ambili K N, Jimmy Jose
Jingchun Yang, Dongdai Lin
Joseph Gravellier, Jean-Max Dutertre, Yannick Teglia, Philippe Loubet Moundi
Joël Gugger
Jing Tian, Bo Wu, Zhongfeng Wang
Artur Mariano, Filipe Cabeleira, Gabriel Falcao, Luís Paulo Santos
Alexandre Adomnicai, Thomas Peyrin
Aggelos Kiayias, Andrianna Polydouri, Dionysis Zindros
Wilson Alberto Torres, Ron Steinfeld, Amin Sakzad, Veronika Kuchta
In this paper, we present a new post-quantum cryptographic mechanism, called Lattice-based Linkable Ring Signature with Co-Signing (L2RS-CS), which offers a distributed authorisation feature to protect electronic wallets. A novel security model for L2RS-CS is also formalised to capture the security and privacy requirements to protect transactions in applications to blockchain cryptocurrency protocols, such as the RingCT. To address key-generation security concerns, and to support compression of keys and signatures, the L2RS-CS incorporates a distributed key generation along with a solid public-key aggregation. Finally, we prove the security of our constructed L2RS-CS in the random oracle model and the standard lattice-based Module-SIS hardness assumption.
Yasufumi Hashimoto
Christoph Hagen, Christian Weinert, Christoph Sendner, Alexandra Dmitrienko, Thomas Schneider
Our study of three popular mobile messengers (WhatsApp, Signal, and Telegram) shows that, contrary to expectations, large-scale crawling attacks are (still) possible. Using an accurate database of mobile phone number prefixes and very few resources, we have queried 10% of US mobile phone numbers for WhatsApp and 100% for Signal. For Telegram we find that its API exposes a wide range of sensitive information, even about numbers not registered with the service. We present interesting (cross-messenger) usage statistics, which also reveal that very few users change the default privacy settings. Regarding mitigations, we propose novel techniques to significantly limit the feasibility of our crawling attacks, especially a new incremental contact discovery scheme that strictly improves over Signal's current approach.
Furthermore, we show that currently deployed hashing-based contact discovery protocols are severely broken by comparing three methods for efficient hash reversal of mobile phone numbers. For this, we also propose a significantly improved rainbow table construction for non-uniformly distributed inputs that is of independent interest.
Andrey Kim, Antonis Papadimitriou, Yuriy Polyakov
We present a reduced-error CKKS variant that removes the approximation errors due to the Learning With Errors (LWE) noise in the encryption and key switching operations. We also propose and implement its RNS instantiation that has a lower error than the original CKKS scheme implementation based on multiprecision integer arithmetic. While formulating the RNS instantiation, we develop an intermediate RNS variant that has a smaller approximation error than the prior RNS variant of CKKS. The high-level idea of our main RNS-specific improvements is to remove the approximate scaling error using an automated procedure that computes different scaling factors for each level and performs all necessary adjustments. The rescaling procedure and scaling factor adjustments in our implementation are done automatically and are not exposed to the application developer.
We implement both RNS variants in PALISADE and compare their approximation error and efficiency to the prior RNS variant. Our results for uniform ternary secret key distribution, which is the most efficient setting included in the community homomorphic encryption security standard, show that the reduced-error CKKS RNS implementation typically has an approximation error that is 6 to 9 bits smaller for computations with multiplications than the prior RNS variant. For computations without a multiplication, the approximation error can be up to 20 bits lower than in the prior RNS variant. As compared to the original CKKS using multiprecision integer arithmetic, our reduced-error CKKS RNS implementation has an error that is smaller by 4 and up to 20 bits for computations with multiplications and without multiplications, respectively. For the sparse ternary secret key setting, which was used in the original CKKS paper, the approximate error reduction of reduced-error CKKS w.r.t. original CKKS typically ranges from 6 to 8 bits for computations with multiplications.
Jia Kan
World widely virtual currency mining was commonly regarded as over energy consuming. How to make use of the computation capacity provided by mining, is one of the most important problems to solve in blockchain. We extend Proof of Work to be useful and economic. And discover a simple method to generate the proof of storing useful data with PoW. In a blockchain based distributed file storage system, any storage resource owner could freely join as a service provider. It requires the service provider to show the proof of honestly keeping the data content, because the malicious provers may use other's content to generate the proof in order to reduce their resource cost. This is out-sourcing attack. Furtherly, we proposed a novel technique to combine data replica process with Proof of Work's contributing to blockchain security.
V. Ustimenko
Karim M. Abdellatif, Olivier Hériveaux
19 September 2020
Information Security Group, Royal Holloway, University of London, UK
The ISG is a nice place to work; it’s a friendly environment with strong research going on in several areas. We got people working across the field of information security including several people working on cryptography. For example, Carlos Cid, Anamaria Costache, Lydia Garms, Jianwei Li, Sean Murphy, Rachel Player, Eamonn Postlethwaite, Joe Rowell, Fernando Virdia and Martin Albrecht all have looked at or are looking at lattice-based cryptography.
The ISG is one of the largest departments dedicated to information security in the world with 21 core academic staff in the department, as well as research and support staff. We work with many research partners in other departments and have circa 90 PhD students working on a wide range of security research, many of whom are fully funded through our Centre for Doctoral Training in Cyber Security. We have a strong, vibrant, embedded and successful multi-disciplinary research profile spanning from cryptography to systems security and social aspects of security. This vibrant environment incorporates visiting researchers, weekly research seminars, weekly reading groups, PhD seminars and mini conferences, the WISDOM group (Women in the Security Domain Or Mathematics) and we are proud of our collegial atmosphere and approach.
A postdoc here is a 100% research position, i.e. the postdoc would not have teaching duties. That said, if the applicant would like to gain some teaching experience, we can arrange for that as well.
Closing date for applications:
Contact: Martin Albrecht
More information: https://martinralbrecht.wordpress.com/2020/09/17/postdoc-at-royal-holloway-on-lattice-based-cryptography-4/
16 September 2020
TU Darmstadt, Germany
Current topics of interest include (but are not limited to):
- Secure cryptographic implementations
- Leakage/tamper resilient cryptography
- Blockchains and cryptocurrencies
- Distributed cryptography
The candidate shall be able to show solid expertise in cryptography/IT Security illustrated in form of publications at major crypto/security venues such as CRYPTO, EUROCRYPT, ASIACRYPT, TCC, PKC, CHES, FC, ACM CCS, Oakland, USENIX Security, NDSS etc.
The position offers an internationally competitive salary including social benefits. TU Darmstadt is a leading university for Computer Science and offers excellent working environment in the heart of the Rhein-Main metropolitan area. It has a strong institute for research on IT security and cryptography with more than 300 researchers working on all aspects of cybersecurity. Review of applications starts immediately until the position is filled.
Closing date for applications:
Contact: sebastian.faust@cs.tu-darmstadt.de
Halifax, Canada, 19 October - 20 October 2020
Villanova University
Requirements: preferred to be at the majors of Computer Science or Computer Engineering. Majoring in Mathematics are also ok. Proficiency in programming languages such as C, C++, Python, and so on is needed. Good at English communication and writing. Great enthusiasm of doing research oriented tasks. Excellent team worker.
Degree: both B.S. and M.S. graduates or similar are warmly welcomed to apply.
Deadline: better to start at Spring 2021 (Fall 2021 is also ok). It is always better to apply as early as possible. Positions are open until they are filled.
Closing date for applications:
Contact: Jiafeng Harvest Xie (jiafeng.xie@villanova.edu)