Background and Definition
Vectorial Boolean Functions play an essential role in the design of cryptographic algorithms, and as such should be resistant to various types of cryptanalytic attacks. The notion of nonlinearity is introduced by Nyberg  in order to measure the resistance of vectorial Boolean functions to Matsui's linear attack . This attack attempts to approximate the function used in an encryption algorithm by a linear function (which, in turn, is easy to analyze), and is, therefore, applicable when the actual functions used in the encryption algorithm is "close" to linear in some sense. A natural measure of distance between two functions, and , is the Hamming distance, i.e. the metric
Formally, the nonlinearity of an -function is the minimum distance between any component function of and any affine Boolean function. In other words,
Nonlinearity remains invariant under CCZ-equivalence (and, therefore, under extended affine and affine equivalence as well). If is -permutation, then and have the same nonlinearity.
The nonlinearity of an -function can be expressed in terms of its Walsh transform via the identity
There is a relation  between the maximal possible nonlinearity of vectorial Boolean functions and the possible parameters of certain linear codes. If is a linear containing the Reed-Muller code as a subcode, let be a basis of completing a basis of . Then the -variable Boolean functions corresponding to the vectors are the coordinate functions of an functions with nonlinearity . Conversely, given an function of nonlinearity , the linear code obtained as the union of all cosets has parameters .
Bounds on the Nonlinearity of Vectorial Boolean Functions
The covering radius bound for Boolean functions can naturally be extended to vectorial Boolean functions, stating
for any -function . Bent Functions are defined as those meeting this bound with equality.
The SCV bound coincides with the covering radius bound for , and is strictly sharper than the covering radius bound for . For , the square root in the bound cannot be an integer, and thus the SCV bound can be, and is, tight only for . In this case (for ), the bound becomes
This motivates the definition of Almost Bent Functions as those -functions that meet the SCV bound with equality.
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- Chabaud F, Vaudenay S. Links between differential and linear cryptanalysis. Workshop on the Theory and Application of Cryptographic Techniques 1994 May 9 (pp. 356-365). Springer, Berlin, Heidelberg.