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It is a form of partitioning cryptanalysis that exploits unevenness in how the cipher operates over equivalence classes (congruence classes) modulo n. The method was first suggested in 1999 by John Kelsey , Bruce Schneier , and David Wagner and applied to RC5P (a variant of RC5 ) and M6 (a family of block ciphers used in the FireWire standard).
Matrix congruence is an equivalence relation. Matrix congruence arises when considering the effect of change of basis on the Gram matrix attached to a bilinear form or quadratic form on a finite-dimensional vector space : two matrices are congruent if and only if they represent the same bilinear form with respect to different bases .
An MDS matrix (maximum distance separable) is a matrix representing a function with certain diffusion properties that have useful applications in cryptography.Technically, an matrix over a finite field is an MDS matrix if it is the transformation matrix of a linear transformation = from to such that no two different (+)-tuples of the form (, ()) coincide in or more components.
One of the most important issues for any cryptographic primitive is the security of the system. However, in numerous cases, chaos-based cryptography algorithms are proved insecure. [5] [8] [9] [10] The main issue in many of the cryptanalyzed algorithms is the inadequacy of the chaotic maps implemented in the system. [11] [12]
Visual cryptography is a cryptographic technique which allows visual information (pictures, text, etc.) to be encrypted in such a way that the decrypted information appears as a visual image. One of the best-known techniques has been credited to Moni Naor and Adi Shamir , who developed it in 1994. [ 1 ]
The following outline is provided as an overview of and topical guide to cryptography: Cryptography (or cryptology) – practice and study of hiding information. Modern cryptography intersects the disciplines of mathematics, computer science, and engineering. Applications of cryptography include ATM cards, computer passwords, and electronic ...
Multivariate cryptography is the generic term for asymmetric cryptographic primitives based on multivariate polynomials over a finite field. In certain cases, those polynomials could be defined over both a ground and an extension field. If the polynomials have degree two, we talk about multivariate quadratics.
The ideas of mutual learning, self learning, and stochastic behavior of neural networks and similar algorithms can be used for different aspects of cryptography, like public-key cryptography, solving the key distribution problem using neural network mutual synchronization, hashing or generation of pseudo-random numbers.