Overview

In the relentless battle against escalating cyber threats, data security faces a critical challenge – the need for innovative solutions to fortify encryption and decryption processes. The increasing frequency and complexity of cyber-attacks demand a dynamic approach, and this is where the intersection of cryptography and machine learning emerges as a powerful ally. As hackers become more adept at exploiting vulnerabilities, the book stands as a beacon of insight, addressing the urgent need to leverage machine learning techniques in cryptography. Machine Learning and Cryptographic Solutions for Data Protection and Network Security unveils the intricate relationship between data security and machine learning and provide a roadmap for implementing these cutting-edge techniques in the field. The book equips specialists, academics, and students in cryptography, machine learning, and network security with the tools to enhance encryption and decryption procedures by offering theoretical frameworks and the latest empirical research findings. Its pages unfold a narrative of collaboration and cross-pollination of ideas, showcasing how machine learning can be harnessed to sift through vast datasets, identify network weak points, and predict future cyber threats. This book is an indispensable guide for scholars navigating the intricate domains of Elliptic Curve Cryptography, Cryptanalysis, Pairing-based Cryptography, Artificial Intelligence, Digital Signature Algorithms, and more. It not only sheds light on current challenges but also provides actionable insights and recommendations, making it an essential resource for those seeking to understand the evolving landscape of data security and actively contribute to its fortification. In a world where the stakes of cybersecurity are higher than ever, this book emerges as a beacon of knowledge, offering a proactive and informed solution to the persistent challenges faced by the research community.

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P. Visalakshi is an Associate Professor at SRM Institute of Science and Technology based in Dist, Tamil Nadu. R. Uma is working as Associate Professor in the Department of Computer Science and Engineering, Sri Sairam Engineering College, Chennai, India. with 23 years of teaching experience for undergraduate and post graduate students in Computer Science Department. She has a Doctorate degree in Computer Science and Engineering from Anna University Chennai, India. She also completed her Master Degree in Computer Science and Engineering from College of Engineering Guindy, Anna University, India and Bachelor Degree from university of Madras. She has published her papers over 14 International Journals. She is a member of CSI, IACSIT and life member of ISTE. Her current research interest includes Information Retrieval, Data Mining, Deep learning and Machine learning .

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