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On the Lower Block Triangular Nature of the Incidence Matrices to Compute the Algebraic Immunity of Boolean Functions

机译:关于计算布尔函数的代数免疫度的关联矩阵的下块三角性质

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The incidence matrix between two sets of vectors in F2 has a great importance in different areas of mathematics and sciences. The rank of these matrices are very useful while computing the algebraic immunity(AI) of Boolean functions in cryptography literature. With a proper ordering of monomial (exponent) vectors and support vectors, some interesting algebraic structures in the incidence matrices can be observed. We have exploited the lower-block triangular structure of these matrices to find their rank. This structure is used for faster computation of the AI and the low degree annihilators of an n-variable Boolean functions than the known algorithms. On the basis of experiments on at least 20 variable Boolean functions, we conjecture about the characterization of power functions of algebraic immunity 1, could verify the result on the AI of n-variable inverse S-box presented in (i.e., |~-2 n~(1/2)| - 2), and presented some results on the AI of some important power S-boxes.
机译:F2中两组向量之间的关联矩阵在数学和科学的不同领域中具有重要意义。这些矩阵的等级在计算密码学文献中布尔函数的代数免疫(AI)时非常有用。通过对单项(指数)向量和支持向量进行适当排序,可以观察到入射矩阵中一些有趣的代数结构。我们已经利用这些矩阵的下块三角结构来找到它们的等级。与已知算法相比,此结构可用于更快地计算AI和n变量布尔函数的低度零化子。在至少20个布尔布尔函数的实验基础上,我们推测代数免疫力1的幂函数的表征可以验证n变量反S盒的AI的结果(即|〜-2 n〜(1/2)| - - 2),并介绍了一些重要动力S盒的AI结果。

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