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24 November 2021
CSEM, Neuchâtel / AAU, Department of Artificial Intelligence and Cybersecurity, Klagenfurt, Austria
You will conduct research towards a distributed intrusion detection system for constrained devices in real-world IoT applications. The intrusion detection system (IDS) you will develop will facilitate detection and containment of a security breach in the Edge, making the IoT applications of tomorrow more secure and reliable.
Your activity will be at an exciting intersection of the following fields:- Embedded development. The constrained nature of low-power embedded world will present you with stimulating research challenges. You will implement and test your results on real-world, low-power embedded HW platforms, maintaining a steady link between your research and practice and ensuring a real-world impact.
- Applied security. To defend from attacks, you will get intimately familiar with them. You will acquire knowledge of different types of intrusion, how they manage to penetrate a system, and how they can be recognized.
- Artificial intelligence. Modern IDS systems rely on AI. You will review the state of the art, select the most viable AI algorithms for an IDS in the constrained setting of IoT Edge, and carefully tweak them for the job.
- Distributed computing. A swarm of Things in the Edge can, collaboratively monitor itself much more effectively than a single device. You will combine all the above and deploy a distributed IDS on a group of constrained embedded devices, identifying the tradeoffs between efficiency and overhead.
We are looking for a student who has a Masters (or equivalent) degree in Electrical Engineering, Electronics or Computer Science with background and passion in (most of):
- Solid understanding of machine learning concepts and some practice
- Proficiency with programming in C
- Experience with embedded development is an advantage
- Background in applied cryptography and security is an advantage
- Fluency in English is required, proficiency in French is an advantage.
- Good communication and interpersonal skills.
Closing date for applications:
Contact: To apply visit https://www.csem.ch/page.aspx?pid=47528&jobid=122842.
You will be based in part at CSEM (Switzerland), and in part at the Cybersecurity Research Group at AAU (Austria); you need to be eligible to work in Europe, and you need to be flexible as you will travel regularly.More information: https://www.csem.ch/page.aspx?pid=47528&jobid=122842
University of Waterloo, Department of Combinatorics and Optimization
The Faculty of Mathematics at the University of Waterloo invites applications from outstanding qualified candidates for two, 2-year, prestigious postdoctoral fellowship positions. Applications are solicited from any of the research areas of the Department of Combinatorics & Optimization: Algebraic Combinatorics, Discrete Optimization, Continuous Optimization, Cryptography, Graph Theory, and Quantum Computing.
A Ph.D. degree and evidence of excellence in research are required. Successful applicants are expected to maintain an active program of research. The annual salary is $75,000. In addition, a travel fund of $15,000 per year is provided. The anticipated start date is fall 2022.
Interested individuals should apply using the MathJobs site (https://www.mathjobs.org/jobs/list/19031). Applications should include a cover letter describing their interest in the position, and names of faculty members with whom the applicant would like to interact, a curriculum vitae and research statement, and at least three reference letters.
Inquiries may be addressed to Jochen Koenemann, Chair, Department of Combinatorics and Optimization. The deadline for application is December 31, 2021.
Closing date for applications:
Contact: Jochen Koenemann (jochen@uwaterloo.ca)
More information: https://uwaterloo.ca/combinatorics-and-optimization/career-opportunities#PrestigiousPDF
University of Leuven (KU LEUVEN)
The prospective candidate will design and develop efficient MPC protocols for privacy-preserving data analytics for medical diagnostics and predictive maintenance applications. The work includes, but is not limited to, investigating machine learning algorithms that best suit MPC and that have efficient implementations over MPC. You will be working closely with tools such as SCALE-MAMBA and/or MP-SPDZ. The candidate will be part of a team in a project on Secure and Scalable Data Sharing, which will run until mid-2025.
Specific skills required:
The candidate must hold a PhD degree in Cryptography or a related subject with strong publication records in crypto/security venues. In addition to a strong background in both public and symmetric cryptography, good knowledge in MPC, machine learning algorithms, and cryptographic protocols are expected. Hands on experience with an MPC framework will be considered as a merit. The candidate should also have coding experience in C/C++ and Python, experience in practical aspects of secure computation is a must.
Closing date for applications:
Contact: Please check the application procedure at https://www.esat.kuleuven.be/cosic/vacancies/ and send all requested documents to jobs-cosic@esat.kuleuven.be
More information: https://www.esat.kuleuven.be/cosic/vacancies/
23 November 2021
Alex Lombardi, Fermi Ma, Nicholas Spooner
In this work, we develop new techniques for quantum rewinding in the context of extraction and zero-knowledge simulation:
(1) We show how to extract information from a quantum adversary by rewinding it without disturbing its internal state. We use this technique to prove that important interactive protocols, such as the Goldreich-Micali-Wigderson protocol for graph non-isomorphism and the Feige-Shamir protocol for NP, are zero-knowledge against quantum adversaries.
(2) We prove that the Goldreich-Kahan protocol for NP is post-quantum zero knowledge using a simulator that can be seen as a natural quantum extension of the classical simulator.
Our results achieve (constant-round) black-box zero-knowledge with negligible simulation error, appearing to contradict a recent impossibility result due to Chia-Chung-Liu-Yamakawa (FOCS 2021). This brings us to our final contribution:
(3) We introduce coherent-runtime expected quantum polynomial time, a computational model that (a) captures all of our zero-knowledge simulators, (b) cannot break any polynomial hardness assumptions, and (c) is not subject to the CCLY impossibility. In light of our positive results and the CCLY negative results, we propose coherent-runtime simulation to be the right quantum analogue of classical expected polynomial-time simulation.
Fahim Rahman, Farimah Farahmandi, Mark Tehranipoor
Shay Gueron, Ashwin Jha, Mridul Nandi
George Teseleanu
22 November 2021
Bar-Ilan University, Israel
This project is in collaboration with Purdue University and participant will be offered several all expenses paid visits to Purdue University, USA.
The postdoctoral position is offered for 1 year and can be extended by an additional year contingent upon funding and satisfactory performance. The PhD position spans an entire course of a PhD degree, with an expected duration of 4 years.
Applicants should ideally have background in information-theoretic secure computation as well as general background in cryptography. Knowledge in coding theory and information theory is an advantage. Candidates are expected to be highly motivated and mathematically capable.
Applications should include (1) a CV including a list of publications, (2) a short research statement, (3) names and contact information of 2-3 potential references.
Closing date for applications:
Contact: carmit.hazay@biu.ac.il and ran.gelles@biu.ac.il
Virginia Tech
Closing date for applications:
Contact: qacc21@math.vt.edu
Virginia Tech
Closing date for applications:
Contact: Gretchen Matthews gmatthews@vt.edu
More information: http://careers.pageuppeople.com/968/cw/en-us/job/518387/postdoctoral-associate-cy-matthews
University of Luxembourg, interdisciplinary centre for security reliability and trust, Luxembourg
Security of Decentralized Finance in Ethereum blockchain.
The successful candidate will closely work with industry, specifically with Quantstamp. The position holder will be required to perform the following tasks:
Closing date for applications:
Contact: Antonio Ken Iannillo
Zeta Avarikioti, Mahsa Bastankhah, Mohammad Ali Maddah-Ali, Krzysztof Pietrzak, Jakub Svoboda, Michelle Yeo
We then present protocols with weaker privacy guarantees but much better efficiency. In particular, route discovery typically only involves small fraction of the nodes but some information on the topology and balances -- beyond what is necessary for performing the transaction -- is leaked.
The core idea is that both sender and receiver gossip a message which then slowly propagates through the network, and the moment any node in the network receives both messages, a path is found. In our first protocol the message is always sent to all neighbouring nodes with a delay proportional to the fees of that edge. In our second protocol the message is only sent to one neighbour chosen randomly with a probability proportional to its degree. While the first instantiation always finds the cheapest path, the second might not, but it involves a smaller fraction of the network.
% We discuss some extensions like employing bilinear maps so the gossiped messages can be re-randomized, making them unlikeable and thus improving privacy. We also discuss some extensions to further improve privacy by employing bilinear maps.
Simulations of our protocols on the Lightning network topology (for random transactions and uniform fees) show that our first protocol (which finds the cheapest path) typically involves around 12\% of the 6376 nodes, while the second only touches around 18 nodes $(<0.3\%)$, and the cost of the path that is found is around twice the cost of the optimal one.
Nishanth Chandran, Divya Gupta, Sai Lakshmi Bhavana Obbattu, Akash Shah
In this work, we design and build SIMC, a new cryptographic system for secure inference in the client malicious threat model. On secure inference benchmarks considered by MUSE, SIMC has 23 − 29× lesser communication and is up to 11.4× faster than MUSE. SIMC obtains these improvements using a novel protocol for non-linear activation functions (such as ReLU) that has > 28× lesser communication and is up to 43× more performant than MUSE. In fact, SIMC's performance beats the state-of-the-art semi-honest secure inference system!
Finally, similar to MUSE, we show how to push the majority of the cryptographic cost of SIMC to an input independent preprocessing phase. While the cost of the online phase of this protocol, SIMC++, is same as that of MUSE, the overall improvements of SIMC translate to similar improvements to the preprocessing phase of MUSE.
Shotaro Miyashita, Ryoma Ito, Atsuko Miyaji
Gang Wang, Mark Nixon
Avik Chakraborti, Nilanjan Datta, Ashwin Jha, Cuauhtemoc Manicillas Lopez, Mridul Nandi
Liang Zhao, Ze Chen, Liqun Chen, Xinyi Huang
Lorenzo Grassi, Dmitry Khovratovich, Sondre Rønjom, Markus Schofnegger
In this paper, we analyze high-degree functions such as the Legendre symbol or the modulo-2 operation as building blocks for the nonlinear layer of a cryptographic scheme over (F_p)^n. Our focus regards the security analysis rather than the efficiency in the mentioned use cases. For this purpose, we present several new invertible functions that make use of the Legendre symbol or of the modulo-2 operation.
Even though these functions often provide strong statistical properties and ensure a high degree after a few rounds, the main problem regards their small number of possible outputs, that is, only three for the Legendre symbol and only two for the modulo-2 operation. By guessing them, it is possible to reduce the overall degree of the function significantly. We exploit this behavior by describing the first preimage attack on full Grendel, and we verify it in practice.
Ingerid Fosli, Yuval Ishai, Victor I. Kolobov, Mary Wootters
* In the case of linear information-theoretic HSS schemes for degree-$d$ multivariate polynomials, we characterize the optimal download rate in terms of the optimal minimal distance of a linear code with related parameters. We further show that for sufficiently large $\ell$ (polynomial in all problem parameters), the optimal rate can be realized using Shamir's scheme, even with secrets over $\mathbb{F}_2$.
* We present a general rate-amplification technique for HSS that improves the download rate at the cost of requiring more shares. As a corollary, we get high-rate variants of computationally secure HSS schemes and efficient private information retrieval protocols from the literature.
* We show that, in some cases, one can beat the best download rate of linear HSS by allowing nonlinear output reconstruction and $2^{-\Omega(\ell)}$ error probability.
Jonathan Prokos, Tushar M. Jois, Neil Fendley, Roei Schuster, Matthew Green, Eran Tromer, Yinzhi Cao
In this work we develop threat models for perceptual hashing algorithms in an adversarial setting, and present attacks against the two most widely deployed algorithms: PhotoDNA and PDQ. Our results show that it is possible to efficiently generate targeted second-preimage attacks in which an attacker creates a variant of some source image that matches some target digest. As a complement to this main result, we also further investigate the production of images that facilitate detection avoidance attacks, continuing a recent investigation of Jain et al. Our work shows that existing perceptual hash functions are likely insufficiently robust to survive attacks on this new setting.