Cryptic Mining in Light of Artificial Intelligence

Abstract

Abstract-"The analysis of cryptic text is hard problem", and there is no fixed algorithm for generating plain-text from cipher text. Human brains do this intelligently. The intelligent cryptic analysis process needs learning algorithms, co-operative effort of cryptanalyst and mechanism of knowledge based inference engine. This information of knowledge base will be useful for mining data(plain-text, key or cipher text plain-text relationships), classification of cipher text based on enciphering algorithms, key length or any other desirable parameters, clustering of cipher text based on similarity and extracting association rules for identifying weaknesses of cryptic algorithms. This categorization will be useful for placing given cipher text into a specific category or solving difficult level of cipher textplain text conversion process. This paper elucidates cipher textplain text process first than utilizes it to create a framework for AI-enabled-Cryptanalysis system. The process demonstrated in this paper attempts to analyze captured cipher from scratch. The system design elements presented in the paper gives all hints and guidelines for development of AI enabled Cryptic analysis tool.

AVK based Cryptosystem and Recent Directions Towards Cryptanalysis

“…In [18], the cryptic algorithm developed from Fibonacci-Q matrix [10,14,15] under various situations say hacker is interested to mine future keys, future key sequences, and probable steady state situation using Markov process. The stochastic analysis and future recommendations for ensuring security is presented in [18,20].…”