Applications of Machine Learning Algorithms in Data Encryption Standards

Abstract

Encryption plays a crucial role in safeguarding sensitive information in today's digital world. The traditional encryption methods rely on mathematical algorithms, such as RSA and AES, for securing data. The proliferation of digital communication and the increasing need for secure data transmission have prompted significant advancements in encryption techniques. As data breaches and cyber threats become more sophisticated, there is an increasing need for robust encryption techniques. Machine learning algorithms, with their ability to adapt and learn from data patterns, have emerged as a valuable tool in enhancing encryption processes. This chapter explores the applications of machine learning algorithms in encryption, highlighting their potential to improve security, speed, and versatility. The authors delve into various aspects, including data encryption, key management, authentication, and intrusion detection, demonstrating how machine learning can contribute to the development of more robust and efficient encryption systems.