Using Coding Techniques to Analyze Weak Feedback Polynomials
(2010) IEEE International Symposium on Information Theory (ISIT), 2010 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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1614409
- author
- Hell, Martin LU
- organization
- publishing date
- 2010
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Proceedings
- pages
- 2523 - 2527
- conference name
- IEEE International Symposium on Information Theory (ISIT), 2010
- conference location
- Austin, Texas, United States
- conference dates
- 2010-06-13 - 2010-06-18
- external identifiers
-
- wos:000287512700507
- scopus:77955697530
- language
- English
- LU publication?
- yes
- additional info
- Available on CD-ROM only
- id
- a3187f5e-3ab9-480b-9b45-5e06d613d07d (old id 1614409)
- date added to LUP
- 2016-04-04 13:42:20
- date last changed
- 2022-01-30 00:45:52
@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}},
url = {{https://lup.lub.lu.se/search/files/6185264/1614418.pdf}},
year = {{2010}},
}