The algebraic degree of Boolean functions (or vectorial Boolean functions) is an important cryptographic parameter that should be computed by fast algorithms. They work in two main ways: (1) by computing the algebraic normal form and then searching the monomial of the highest degree in it, or (2) by examination the algebraic properties of the true table vector of a given function. We have already done four basic steps in the study of the first way, and the second one has been studied by other authors. Here we represent a method for fast computing (the fastest way we know) the algebraic degree of Boolean functions. It is a combination of the most efficient components of these two ways and the corresponding algorithms. The theoretical time complexities of the method are derived in each of the cases when the Boolean function is represented in a byte-wise or in a bitwise manner. They are of the same type $Θ(n.2^n)$ for a Boolean function of $n$ variables, but they have big differences between the constants in $Θ$-notation. The theoretical and experimental results shown here demonstrate the advantages of the bitwise approach in computing the algebraic degree - they are dozens of times faster than the byte-wise approaches.
On $2k$-Variable Symmetric Boolean Functions with Maximum Algebraic Immunity $k$
布尔函数$f$的代数免疫定义为非零$g$使得$fg=0$或$(f+1)g=0$的最小次数.给定一个正偶数$n$，发现任何具有最大代数免疫度的$n$变量对称布尔函数$\frac{n}{2}$的权重分布都由$n$的二进制展开决定。在此基础上，构造了所有具有最大代数免疫度的$n$变量对称布尔函数.金额为$(2\wt(n)+1)2^{\lfloor \log_2 n \rfloor}$
Use of Simple Arithmetic Operations to Construct Efficiently Implementable Boolean functions Possessing High Nonlinearity and Good Resistance to Algebraic Attacks
