Description
Data security is paramount in our modern world, and the symbiotic relationship between machine learning and cryptography has recently taken center stage. The vulnerability of traditional cryptosystems to human error and evolving cyber threats is a pressing concern. The stakes are higher than ever, and the need for innovative solutions to safeguard sensitive information is undeniable.
Innovative Machine Learning Applications for Cryptography emerges as a steadfast resource in this landscape of uncertainty. Machine learning's prowess in scrutinizing data trends, identifying vulnerabilities, and constructing adaptive analytical models offers a compelling solution. The book explores how machine learning can automate the process of constructing analytical models, providing a continuous learning mechanism to protect against an ever-increasing influx of data.
This book goes beyond theoretical exploration, and provides a comprehensive resource designed to empower academic scholars, specialists, and students in the fields of cryptography, machine learning, and network security. Its broad scope encompasses encryption, algorithms, security, and more unconventional topics like Quantum Cryptography, Biological Cryptography, and Neural Cryptography. By examining data patterns and identifying vulnerabilities, it equips its readers with actionable insights and strategies that can protect organizations from the dire consequences of security breaches.
Author's/Editor's Biography
J. Ruth (Ed.)
Dr. J. Anitha Ruth is an Associate Professor at SRM Institute of Science and Technology in Chennai, where she teaches courses in Computer Science and Applications at the Vadapalani Campus. In the field of Computer Science, she has been an educator for over 22 years, both at the undergraduate and graduate levels . Ph.D. in computer science and engineering from SRMIST is her credential. She is a Bachelor of Science and Master of Science graduate of the University of Madras. In addition to filing other patents, she has published articles in prestigious journals. The has written more than two textbooks and numerous chapters for other books. She is Life time member of Indian Science Congress , Computer Society of India. Sharing her knowledge with students from all walks of life has always been something she has taken pleasure in doing as a teacher. With her background as a teacher and career counselor, she has helped countless students find fulfilling paths to professional success. In her studies, she focuses on neural networks, security, and Deep learning.
G.V. Vijayalakshmi (Ed.)
Vijayalakshmi G V Mahesh
received her BE in Electronics and Communication Engineering from Bangalore University, India in 1999, and M.Tech in Digital Communication and Networking from Visvesvaraya Technological University in 2005 and the Ph.D. degree from the Vellore Institute of Technology, Vellore, India. Currently she is working as an Associate Professor at BMS Institute of Technology and Management, Bangalore, India. She has been in academics for over 19 years and has published her research in various reputed journals and conferences. Her research interests include Machine Learning, Image Processing, Pattern Recognition and Deep learning, Affective computing. She has Memberships in Professional Bodies such as ISTE and IEI.
P. Visalakshi (Ed.)
|P. Visalakshi - Editor|N/A
R. Uma (Ed.)
|R. Uma - Editor|N/A
A. Meenakshi (Ed.)
Dr. A. Meenakshi serves as Head of the Department of Computer Science and Applications M.C.A at SRM Institute of Science and Technology, Vadapalani Campus, Chennai. With over 24 years of teaching experience, she holds a Doctorate degree in Computer Science and Engineering. Her research encompasses Distributed Computing, Cloud Computing, Machine Learning, Deep Learning, and Data Analytics. She has made notable contributions with publications in esteemed journals, holds three patents, and is currently guiding two research scholars. She is a lifetime member of CSI, ACM, and the Indian Science Congress.