论文标题
地图的局部反转:黑匣子密码分析
Local Inversion of maps: Black box Cryptanalysis
论文作者
论文摘要
本文是在先前的有关一种新的通用性方法中宣布的结果的简短夏季,该方法使用黑匣子线性代数方法来计算有限领域的非线性图的局部反转。结果表明,可以通过使用迭代(或递归)$ y(k+1)= y(y(y(k))$使用$ y(y(0)= y y时,peculsion $ y(y(k))= y $ n时,可以使用序列定义的序列$ y(k)$ y = y $时,可以使用序列$ y(k)$定义的序列$ y(k)$ y = y = f(x)$的一个本地逆$ x $计算。这是地图$ f $的周期性轨道中唯一的解决方案。此外,当最小多项式的程度在$ f $(称为低复杂性案例)的输入的位数中为多项式顺序时,可以在多项式时间内计算解决方案。计算方法仅对给定的$ y $使用远期计算$ f(y)$,这就是为什么这被称为黑匣子方法的原因。然后,显示了这种方法的应用,用于密码图中产生的几个地图的密码分析。它显示了如何在低复杂性案例中映射由块和流密码定义的映射,以在已知的明文攻击下找到对称键。然后,它显示了如何倒入RSA映射以找到明文以及等效的私钥,以破坏RSA算法而无需考虑模量。最后,结果表明,有限场和椭圆曲线中的离散对数计算可以作为局部反转问题进行配合,并且可以在多项式时间内求解低复杂性情况。
This paper is a short summery of results announced in a previous paper on a new universal method for Cryptanalysis which uses a Black Box linear algebra approach to computation of local inversion of nonlinear maps in finite fields. It is shown that one local inverse $x$ of the map equation $y=F(x)$ can be computed by using the minimal polynomial of the sequence $y(k)$ defined by iterates (or recursion) $y(k+1)=F(y(k))$ with $y(0)=y$ when the sequence is periodic. This is the only solution in the periodic orbit of the map $F$. Further, when the degree of the minimal polynomial is of polynomial order in number of bits of the input of $F$ (called low complexity case), the solution can be computed in polynomial time. The method of computation only uses the forward computations $F(y)$ for given $y$ which is why this is called a Black Box approach. Application of this approach is then shown for cryptanalysis of several maps arising in cryptographic primitives. It is shown how in the low complexity cases maps defined by block and stream ciphers can be inverted to find the symmetric key under known plaintext attack. Then it is shown how RSA map can be inverted to find the plaintext as well as an equivalent private key to break the RSA algorithm without factoring the modulus. Finally it is shown that the discrete log computation in finite field and elliptic curves can be formulated as a local inversion problem and the low complexity cases can be solved in polynomial time.