Paper Info
Title
Maximum Autocorrelation Analysis of Nonlinear Combining Functions in Stream Ciphers
Abstract
This paper investigates two new design rules of nonlinear combining functions in stream ciphers. It is shown that a combining function with high nonlinearity and high order correlation immunity is still not enough to prevent the divide and conquer attack and the BAA attack (or the best affine approximation attack) since the autocorrelation function of the combining function may also be leaked much more information about the input of the combining function. To measure the strength of nonlinear combining functions, the notion of maximum autocorrelation is introduced, which is based on the correlation between linear functions of input and the autocorrelation function of a combining function. The relationship between the maximum autocorrelation coefficient and the mutual information of the autocorrelation function of the combining function is discussed. Moreover, the upper bound of maximum autocorrelation coefficient is presented by using Walsh transform.
Year
DOI
Venue
2007
10.1109/ISIT.2007.4557083
ISIT
Keywords
Field
DocType
stream ciphers,walsh functions,autocorrelation function,cryptography,nonlinear combining functions,baa attack,maximum autocorrelation analysis,walsh transform,divide and conquer attack,transforms,divide and conquer methods,correlation methods,high order correlation immunity,autocorrelation,random variables,upper bound,divide and conquer,information security,mutual information,boolean functions,generators,correlation,design rules,stream cipher,shift registers
Discrete mathematics,Correlation immunity,Maximum entropy spectral estimation,Random variable,Autocorrelation technique,Autocorrelation matrix,Walsh function,Moving-average model,Mathematics,Autocorrelation
Conference
Volume
Issue
ISSN
null
null
null
ISBN
Citations 
PageRank 
978-1-4244-1397-3
1
0.37
References 
Authors
3
2
Name
Order
Citations
PageRank
Yongzhuang Wei16916.94
Yupu Hu243061.99