Towards Faster Polynomial-Time Lattice Reduction

Author(s):  
Paul Kirchner ◽  
Thomas Espitau ◽  
Pierre-Alain Fouque
2020 ◽  
Vol 31 (02) ◽  
pp. 207-231
Author(s):  
Hatem M. Bahig ◽  
Dieaa I. Nassr ◽  
Ashraf Bhery ◽  
Abderrahmane Nitaj

Let [Formula: see text] be an RSA public key with private exponent [Formula: see text] where [Formula: see text] and [Formula: see text] are large primes of the same bit size. At Eurocrypt 96, Coppersmith presented a polynomial-time algorithm for finding small roots of univariate modular equations based on lattice reduction and then succussed to factorize the RSA modulus. Since then, a series of attacks on the key equation [Formula: see text] of RSA have been presented. In this paper, we show that many of such attacks can be unified in a single attack using a new notion called Coppersmith’s interval. We determine a Coppersmith’s interval for a given RSA public key [Formula: see text] The interval is valid for any variant of RSA, such as Multi-Prime RSA, that uses the key equation. Then we show that RSA is insecure if [Formula: see text] provided that we have approximation [Formula: see text] of [Formula: see text] with [Formula: see text] [Formula: see text] The attack is an extension of Coppersmith’s result.


2018 ◽  
Vol 60 (2) ◽  
pp. 360-375
Author(s):  
A. V. Vasil'ev ◽  
D. V. Churikov

10.29007/v68w ◽  
2018 ◽  
Author(s):  
Ying Zhu ◽  
Mirek Truszczynski

We study the problem of learning the importance of preferences in preference profiles in two important cases: when individual preferences are aggregated by the ranked Pareto rule, and when they are aggregated by positional scoring rules. For the ranked Pareto rule, we provide a polynomial-time algorithm that finds a ranking of preferences such that the ranked profile correctly decides all the examples, whenever such a ranking exists. We also show that the problem to learn a ranking maximizing the number of correctly decided examples (also under the ranked Pareto rule) is NP-hard. We obtain similar results for the case of weighted profiles when positional scoring rules are used for aggregation.


2014 ◽  
Vol 35 (8) ◽  
pp. 1940-1945 ◽  
Author(s):  
Xiang-hui Liu ◽  
Wen-bao Han ◽  
Jian-xiao Quan

Author(s):  
Yishay Mor ◽  
Claudia V. Goldman ◽  
Jeffrey S. Rosenschein
Keyword(s):  

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