Application of Cryptography using Artificial Intelligence

Title: Application of Cryptography using Artificial Intelligence
Publisher: Guru Nanak Publications
ISSN: 2249-9946
Series: Volume 11 Issue 1
Authors: Kritika Purohit


This article addresses some of the recent developments in the area of Cryptography utilizing Artificial Intelligence (AI). The paper introduces detailed thoughts of the current researchers' about how Machine Learning and Evolutionary Computation can be applied to our results. In a quick description, Deep ANNs are briefly introduced, and the concepts of deep learning utilizing deep ANNs are defined. The paper deals with the implementation of the EC and ANNs for the development of unique and unclonable ciphers in this context, and with the ML techniques for the identification of the actual randomness of finite binary strings for Cryptanalysis applications. The aim of this article is to provide a description of how AI may be used to encrypt data and perform cryptanalysis of such data, for determining cryptogram intensity of an encryption algorithm, e.g. in order to identify trends in captured streaming data which are signatures of encrypted data. The majority of this article was published by one or more of the writers who have already contributed to developing behavior analysis. Applications are built that lets you track the numerical worth of different bills, securities, and bonds to avoid counterfeiting. Such variety accounts for new products involving using the phone's antenna to read (in the close field) a versatile radio frequency tag that couples to an integrated circuit with a non-programmable coprocessor. The coprocessor stores ultra-strong encrypted information produced using EC that can be decrypted on-line, thus checking the credibility of the document’s validity across the Internet of Things with a Smartphone. The optical device is intended to function as a visual recognition system for a smart phone by utilizing optical ciphers.


Evolutionary Computing, Optical Authentication, Radiofrequency Identification, Machine Learning, Cryptography, Artificial Intelligence, Artificial Neural Networks.

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