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05 April 2023
Samuel Bedassa Alemu, Julia Kastner
Fuyuki Kitagawa, Tomoyuki Morimae, Ryo Nishimaki, Takashi Yamakawa
Eric Sageloli, Pierre Pébereau, Pierrick Méaux, Céline Chevalier
Sagnik Saha, Nikolaj Ignatieff Schwartzbach, Prashant Nalini Vasudevan
The feasibility and complexity of these problems depends on the relative values of $k$, $r$, and $M$. The dense regime of $M \leq r^k$, where solutions exist with high probability, is quite well-understood and we have several non-trivial algorithms and hardness conjectures here. Much less is known about the sparse regime of $M\gg r^k$, where solutions are unlikely to exist. The best answers we have for many fundamental questions here are limited to whatever carries over from the dense or worst-case settings.
We study the planted $k$-SUM and $k$-XOR problems in the sparse regime. In these problems, a random solution is planted in a randomly generated instance and has to be recovered. As $M$ increases past $r^k$, these planted solutions tend to be the only solutions with increasing probability, potentially becoming easier to find. We show several results about the complexity and applications of these problems.
Conditional Lower Bounds. Assuming established conjectures about the hardness of average-case (non-planted) $k$-SUM when $M = r^k$, we show non-trivial lower bounds on the running time of algorithms for planted $k$-SUM when $r^k\leq M\leq r^{2k}$. We show the same for $k$-XOR as well.
Search-to-Decision Reduction. For any $M>r^k$, suppose there is an algorithm running in time $T$ that can distinguish between a random $k$-SUM instance and a random instance with a planted solution, with success probability $(1-o(1))$. Then, for the same $M$, there is an algorithm running in time $\tilde{O}(T)$ that solves planted $k$-SUM with constant probability. The same holds for $k$-XOR as well.
Hardness Amplification. For any $M \geq r^k$, if an algorithm running in time $T$ solves planted $k$-XOR with success probability $\Omega(1/\text{polylog}(r))$, then there is an algorithm running in time $\tilde O(T)$ that solves it with probability $(1-o(1))$. We show this by constructing a rapidly mixing random walk over $k$-XOR instances that preserves the planted solution.
Cryptography. For some $M \leq 2^{\text{polylog}(r)}$, the hardness of the $k$-XOR problem can be used to construct Public-Key Encryption (PKE) assuming that the Learning Parity with Noise (LPN) problem with constant noise rate is hard for $2^{n^{0.01}}$-time algorithms. Previous constructions of PKE from LPN needed either a noise rate of $O(1/\sqrt{n})$, or hardness for $2^{n^{0.5}}$-time algorithms.
Algorithms. For any $M \geq 2^{r^2}$, there is a constant $c$ (independent of $k$) and an algorithm running in time $r^c$ that, for any $k$, solves planted $k$-SUM with success probability $\Omega(1/8^k)$. We get this by showing an average-case reduction from planted $k$-SUM to the Subset Sum problem. For $r^k \leq M \ll 2^{r^2}$, the best known algorithms are still the worst-case $k$-SUM algorithms running in time $r^{\lceil{k/2}\rceil-o(1)}$.
Nouri Alnahawi, Nicolai Schmitt, Alexander Wiesmaier, Andreas Heinemann, Tobias Grasmeyer
Yiping Ma, Jess Woods, Sebastian Angel, Antigoni Polychroniadou, Tal Rabin
Martin R. Albrecht, Sofía Celi, Benjamin Dowling, Daniel Jones
Kamyar Mohajerani, Luke Beckwith, Abubakr Abdulgadir, Eduardo Ferrufino, Jens-Peter Kaps, Kris Gaj
Uddipana Dowerah, Subhranil Dutta, Aikaterini Mitrokotsa, Sayantan Mukherjee, Tapas Pal
Buvana Ganesh, Apurva Vangujar, Alia Umrani, Paolo Palmieri
Johannes Ernst, Aikaterini Mitrokotsa
- We model privacy preserving biometric based two-factor authentication as an ideal functionality in the UC framework. To the best of our knowledge, this is the first description of an ideal functionality for biometric based two-factor authentication in the UC framework. - We propose a general protocol that uses functional encryption and prove that it UC-realizes our ideal functionality. - We show how to instantiate our framework with efficient, state of the art inner-product functional encryption. This allows the computation of the Euclidean distance, Hamming distance or cosine similarity between encrypted biometric templates. In order to show its practicality, we implemented our protocol and evaluated its performance.
Adda-Akram Bendoukha, Oana Stan, Renaud Sirdey, Nicolas Quero, Luciano Freitas
Hiroki Okada, Kazuhide Fukushima, Shinsaku Kiyomoto, Tsuyoshi Takagi
Hyeonbum Lee, Jae Hong Seo
Yodai Watanabe
Muhammad Imran
04 April 2023
Fredericton, Canada, 16 August - 18 August 2023
Submission deadline: 16 May 2023
Notification: 3 July 2023
Cryptographer Internship
What You'll Do:
Our Ideal Candidate Will:
Closing date for applications:
Contact: Please send your CV to research-jobs@dfns.co Contact Xianrui Meng (xm@dfns.co) and Jon Katz (jkatz@dfns.co) for more information.
SUTD, Singapore
We are looking for postdocs / research fellows with expertise on cybersecurity in general and CPS security in particular. The candidates should meet the following requirements.
Fresh PhD graduates are welcome to apply. Only short-listed candidates will be contacted for interview. Successful candidates will be offered internationally competitive remuneration.
Interested candidates please send your CV to Prof. Jianying Zhou. Email: jianying_zhou (at) sutd.edu.sg. Home: http://jianying.space/
Closing date for applications:
Contact: Prof. Jianying Zhou [jianying_zhou@sutd.edu.sg]
More information: http://jianying.space/
03 April 2023
Prague, Czech Republic, 10 September 2023
Submission deadline: 1 June 2023
Notification: 31 July 2023