IACR News
Here you can see all recent updates to the IACR webpage. These updates are also available:
21 February 2019
University of Warwick
For informal inquiries, please contact Professor Feng Hao, feng.hao (at) warwick.ac.uk, enclosing a CV and a short description of your relevant background and interests.
The Computer Science Department at Warwick is a leading department in the UK. In the 2014 Research Evaluation Framework (REF) which all UK universities participated in, Warwick computer science was ranked the 1st in terms of research output, 2nd in terms of impact and 2nd overall. It is also highly regarded for its research culture, informal environment, excellent students, and beautiful campus.
Closing date for applications: 1 August 2019
More information: https://warwick.ac.uk/fac/sci/dcs/admissions/postgraduateresearch/researchstudentships/?newsItem=8a1785d769003af00169015
Norwegian University of Science and Technology (NTNU)
Closing date for applications: 1 May 2019
Contact: Staal A. Vinterbo, Staal.Vinterbo (at) ntnu.no
More information: https://www.jobbnorge.no/en/available-jobs/job/163521/
Ulm University, Germany
For more details and application portal, see URL below
Closing date for applications: 14 March 2019
Contact: Prof. Dr. Frank Kargl, https://www.uni-ulm.de/in/vs/inst/team/frank-kargl/
More information: https://stellenangebote.uni-ulm.de/jobposting/95503659d66923316e3b202e35ce7405db5365d1
HP Labs, Bristol, UK
Our industrial research lab is a unique environment at the intersection between academic research and real-world innovation in partnership with HP global business units. We provide interns with a unique opportunity to learn about the realities of both worlds, and to contribute research that may eventually impact the HP products and solutions used by millions of people across the globe.
Internships will start between February and July 2019, for a preferred duration of 5-6 months.
We welcome applications from full time students with the relevant skills and experience at Masters and PhD level.
Closing date for applications: 31 March 2019
Contact: Philippa Bayley
Security Lab Operations Manager
philippa.bayley (at) hp.com
More information: https://h30631.www3.hp.com/job/bristol/hp-security-lab-intern/3544/10307305
M. Sadegh Riazi, Mohammad Samragh, Hao Chen, Kim Laine, Kristin Lauter, Farinaz Koushanfar
We design a user-friendly high-level API for XONN, allowing expression of the deep learning model architecture in an unprecedented level of abstraction. We further provide a compiler to translate the model description from high-level Python (i.e., Keras) to that of XONN. Extensive proof-of-concept evaluation on various neural network architectures demonstrates that XONN outperforms prior art such as Gazelle (USENIX Security'18) by up to 7×, MiniONN (ACM CCS'17) by 93×, and SecureML (IEEE S&P'17) by 37×. State-of-the-art frameworks require one round of interaction between the client and the server for each layer of the neural network, whereas, XONN requires a constant round of interactions for any number of layers in the model. XONN is first to perform oblivious inference on Fitnet architectures with up to 21 layers, suggesting a new level of scalability compared with state-of-the-art. Moreover, we evaluate XONN on four datasets to perform privacy-preserving medical diagnosis. The datasets include breast cancer, diabetes, liver disease, and Malaria.
20 February 2019
You can register online at https://secure.iacr.org/conferences/fse2019/register/.
FSE 2019 will take place in Paris, France during March 25-28, 2019. For more information on the conference please visit https://fse.iacr.org/2019.
Lingyue Qin, Xiaoyang Dong, Keting Jia, Rui Zong
Johannes Blömer, Jan Bobolz, Denis Diemert, Fabian Eidens
In this paper, we (1) formally define UACS and their security, (2) give a generic construction for UACS supporting arbitrary update functions, and (3) construct a practically efficient incentive system using UACS.
Stjepan Picek, Annelie Heuser, Sylvain Guilley
Shuwen Deng, Wenjie Xiong, Jakub Szefer
Luca De Feo, Simon Masson, Christophe Petit, Antonio Sanso
Martin R. Albrecht, Torben Brandt Hansen, Kenneth G. Paterson
Hendrik Eerikson, Claudio Orlandi, Pille Pullonen, Joonas Puura, Mark Simkin
In this paper we present the first fully-fledged implementation of an MPC framework that can evaluate arithmetic circuits with arbitrary word sizes. Our framework is based on a new protocol, which improves the communication overhead of the best known previous solutions by a factor of two. We provide extensive benchmarks of our framework in a LAN and in different WAN settings, showing that the online overhead for achieving active security is less than two, when compared to the best solutions for the same setting with passive security. Concretely, for the case of 32- and 64-bit words, we show that our framework can evaluate $10^6$ multiplication gates per second.
Melissa Azouaoui, Romain Poussier, François-Xavier Standaert
Palash Sarkar
Reduction of the time for confirmation of a transaction and speeding up the overall rate of transactions processing without reducing the time for mining a block.
Encourage cooperative behaviour among the miners so that the reward for mining a block is shared by a number of miners.
Use of hardware incompatible hash functions for various stages so that it becomes very difficult for a single entity to attain major computational advantage over all the stages of the block mining.
Improve security by making 51\% attacks more difficult to achieve and by providing resilience to selfish mining attacks.
We believe that the new blockchain structure mitigates the problem of scalability without compromising security. By enforcing cooperative behaviour among the miners, reward for mining a block is more equitably distributed. This, in turn, will help in ensuring participation by a greater number of entities in the overall mining activity.
Andrea Francesco Iuorio, Andrea Visconti
Sujoy Sinha Roy, Furkan Turan, Kimmo Jarvinen, Frederik Vercauteren, Ingrid Verbauwhede
Chen-Da Liu-Zhang, Julian Loss, Ueli Maurer, Tal Moran, Daniel Tschudi
This paper proposes a new, composable model (of UC functionalities) capturing the best of both worlds. Each party obtains the output as fast as the network allows (a property called responsiveness), and it is guaranteed that all parties obtain the same output. We consider different corruption thresholds: correctness, privacy, and responsiveness are guaranteed for less than $T_C$, $T_P$, and $T_R$ corruptions, respectively, while termination is always guaranteed. We achieve a trade-off between correctness, privacy and responsiveness: For any $T_R\leq\frac{1}{3}n$, one can achieve $T_C = T_P=\min\{\frac{1}{2}n,n-2T_R\}$. In particular, setting $T_R = \frac{1}{4}n$ allows us to obtain $T_C = T_P = \frac{1}{2}n$, hence achieving substantial responsiveness, yet correctness and privacy much better than in an asynchronous protocol and as good as for a purely synchronous (slow) protocol.
This result is achieved by a black-box compiler for combining an asynchronous and a synchronous protocol, involving new protocol techniques that may have applications in other contexts, and by devising an asynchronous protocol with $T_C = T_P = n-2T_R$, improving the correctness and privacy of known protocols achieving $T_C=T_P=\frac{1}{3}n$.
Chris Peikert, Sina Shiehian
Our main technical contribution is a hash family that is correlation intractable for arbitrary size-$S$ circuits, for any polynomially bounded $S$, based on plain LWE (with small polynomial approximation factors). The construction combines two novel ingredients: a correlation-intractable hash family for log-depth circuits based on LWE (or even the potentially harder Short Integer Solution problem), and a ``bootstrapping'' transform that uses (leveled) FHE to promote correlation intractability for the FHE decryption circuit to arbitrary (bounded) circuits. Our construction can be instantiated in two possible ``modes,'' yielding a NIZK that is either computationally sound and statistically zero knowledge in the common random string model, or vice-versa in the common reference string model.