NDLI: A New Correlation Attack on Nonlinear Combining Generators

Content Provider	IEEE Xplore Digital Library
Author	Yongzhuang Wei Pasalic, E. Yupu Hu
Copyright Year	1963
Abstract	In this paper, the correlation properties of a nonlinear combining function over its support or zero set are investigated. Based on this characterization, a new attack on nonlinear combining generators is proposed. Our attack does not utilize traditional (non)linear statistics between the input and the output over the entire variable space, as the distinguishing process is rather applied to the restricted input space. The attack appears to be very efficient against nonlinear combining generators whose combining LFSRs are of relatively small input size. In many cases, our attack is a more favorable alternative than the known correlation attacks (but also than algebraic attacks in certain cases). To study the maximum correlation of a nonlinear combining function over its support or zero set, the notion of maximum distinguishable correlation is introduced. The relationship between the maximum distinguishable correlation and the nonlinearity of a combining function is then derived by using the normalized Walsh transform. Finally, we extend the usual notion of resiliency and discuss its implications towards the resistance against our attack.
Sponsorship	IEEE Information Theory Society
Starting Page	6321
Ending Page	6331
Page Count	11
File Size	266475
File Format	PDF
ISSN	00189448
Volume Number	57
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Correlation Boolean functions Generators Cryptography Input variables Random variables Complexity theory stream cipher Correlation attack distinguishable correlation nonlinear combining generator
Content Type	Text
Resource Type	Article
Subject	Library and Information Sciences Information Systems Computer Science Applications

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