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Introduction to Modern Cryptography and Machine Learning
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Author(s): Preeti Mariam Mathews (MIT Mahaguru Institute of Technology, India), Anjali Sandeep Gaikwad (Bharati Vidyapeeth, India), Mathu Uthaman (Mahaguru Institute of Technology, India), B. Sreelekshmi (Mahaguru Institute of Technology, India)and V. Dankan Gowda (BMS Institute of Technology and Management, India)
Copyright: 2024
Pages: 26
Source title:
Innovative Machine Learning Applications for Cryptography
Source Author(s)/Editor(s): J. Anitha Ruth (SRM Institute of Science and Technology, Vadapalani, India), G.V. Mahesh Vijayalakshmi (BMS Institute of Technology and Management, India), P. Visalakshi (Department of Networking and Communications, College of Engineering and Technology, SRM Institute of Science and Technology, Katankulathur, India), R. Uma (Sri Sairam Engineering College, Chennai, India)and A. Meenakshi (SRM Institute of Science and Technology, Vadapalani, India)
DOI: 10.4018/979-8-3693-1642-9.ch001
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Abstract
Cryptography and machine learning are part of mega-tech today. The whole of this chapter is about digital currencies. This is what will happen in the encryption world. First, the authors show how to use PMBeast-1 for something and then later on with bitcoin cryptography where information privacy is concerned. The objective of cryptography is to make data impossible for a human eye by encryption so that only someone in possession of the secret key can determine their length. Yet cryptography is ancient. But actually, it's only within the last few hundred years that their methods and purpose have completely changed. Later parts of this chapter review some recent advances in areas such as symmetric and asymmetric encryption, public-key infrastructure (PKI), and cryptographic hashes. In this way, information becomes one's tutor—machine-like learning. The only difference is that we want these next-generation machines to understand the process of machine learning so as to enhance encryption systems.
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