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Using Coding Techniques to Analyze Weak Feedback Polynomials

Hell, Martin LU (2010) IEEE International Symposium on Information Theory (ISIT), 2010 In Proceedings p.2523-2527
Abstract
We consider a class of weak feedback polynomials for LFSRs in the nonlinear combiner. When feedback taps are located in small groups, a distinguishing attack can sometimes be improved considerably, compared to the common attack that uses low weight multiples. This class of weak polynomials was introduced in 2004 and the main property of the attack is that the noise variables are represented as vectors. We analyze the complexity of the attack using coding theory. We show that the groups of polynomials can be seen as generator polynomials of a convolutional code. Then, the problem of finding the attack complexity is equivalent to finding the minimum row distance of the corresponding generator matrix. A modified version of BEAST is used to... (More)
We consider a class of weak feedback polynomials for LFSRs in the nonlinear combiner. When feedback taps are located in small groups, a distinguishing attack can sometimes be improved considerably, compared to the common attack that uses low weight multiples. This class of weak polynomials was introduced in 2004 and the main property of the attack is that the noise variables are represented as vectors. We analyze the complexity of the attack using coding theory. We show that the groups of polynomials can be seen as generator polynomials of a convolutional code. Then, the problem of finding the attack complexity is equivalent to finding the minimum row distance of the corresponding generator matrix. A modified version of BEAST is used to search all encoders of memory up to 13. Moreover, we give a tight upper bound on the required size of the vectors in the attack. (Less)
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publication status
published
subject
in
Proceedings
pages
2523 - 2527
conference name
IEEE International Symposium on Information Theory (ISIT), 2010
external identifiers
  • wos:000287512700507
  • scopus:77955697530
language
English
LU publication?
yes
id
a3187f5e-3ab9-480b-9b45-5e06d613d07d (old id 1614409)
date added to LUP
2010-06-11 07:50:02
date last changed
2017-01-01 08:13:48
@inproceedings{a3187f5e-3ab9-480b-9b45-5e06d613d07d,
  abstract     = {We consider a class of weak feedback polynomials for LFSRs in the nonlinear combiner. When feedback taps are located in small groups, a distinguishing attack can sometimes be improved considerably, compared to the common attack that uses low weight multiples. This class of weak polynomials was introduced in 2004 and the main property of the attack is that the noise variables are represented as vectors. We analyze the complexity of the attack using coding theory. We show that the groups of polynomials can be seen as generator polynomials of a convolutional code. Then, the problem of finding the attack complexity is equivalent to finding the minimum row distance of the corresponding generator matrix. A modified version of BEAST is used to search all encoders of memory up to 13. Moreover, we give a tight upper bound on the required size of the vectors in the attack.},
  author       = {Hell, Martin},
  booktitle    = {Proceedings},
  language     = {eng},
  pages        = {2523--2527},
  title        = {Using Coding Techniques to Analyze Weak Feedback Polynomials},
  year         = {2010},
}