Enhancing Steganography Through Deep Learning Approaches

Shakila Basheer

ISBN 13: 9798369322239

Published by IGI Global, 2024

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - In an era defined by digital connectivity, securing sensitive information against cyber threats is a pressing concern. As digital transmission systems advance, so do the methods of intrusion and data theft. Traditional security measures often need to catch up in safeguarding against sophisticated cyber-attacks. This book presents a timely solution by integrating steganography, the ancient art of concealing information, with cutting-edge deep learning techniques. By blending these two technologies, the book offers a comprehensive approach to fortifying the security of digital communication channels. Enhancing Steganography Through Deep Learning Approaches addresses critical issues in national information security, business and personal privacy, property security, counterterrorism, and internet security. It thoroughly explores steganography's application in bolstering security across various domains. Readers will gain insights into the fusion of deep learning and steganography for advanced encryption and data protection, along with innovative steganographic techniques for securing physical and intellectual property. The book also delves into real-world examples of thwarting malicious activities using deep learning-enhanced steganography. This book is tailored for academics and researchers in Artificial Intelligence, postgraduate students seeking in-depth knowledge in AI and deep learning, smart computing practitioners, data analysis professionals, and security sector professionals.

Seller Inventory # 9798369322239

Bibliographic Details

• Title: Enhancing Steganography Through Deep Learning Approaches
• Publisher: IGI Global
• Publication Date: 2024
• Language: English
• ISBN 13: 9798369322239
• Binding: Buch
• Condition: Neu
• Dimensions: 260W x 183H x 28D millimeters 260 millimeters width by 183 millimeters height by 28 millimeters depth
• Weight: 1006 grams

About this title

Synopsis

In an era defined by digital connectivity, securing sensitive information against cyber threats is a pressing concern. As digital transmission systems advance, so do the methods of intrusion and data theft. Traditional security measures often need to catch up in safeguarding against sophisticated cyber-attacks. This book presents a timely solution by integrating steganography, the ancient art of concealing information, with cutting-edge deep learning techniques. By blending these two technologies, the book offers a comprehensive approach to fortifying the security of digital communication channels. Enhancing Steganography Through Deep Learning Approaches addresses critical issues in national information security, business and personal privacy, property security, counterterrorism, and internet security. It thoroughly explores steganography's application in bolstering security across various domains. Readers will gain insights into the fusion of deep learning and steganography for advanced encryption and data protection, along with innovative steganographic techniques for securing physical and intellectual property. The book also delves into real-world examples of thwarting malicious activities using deep learning-enhanced steganography. This book is tailored for academics and researchers in Artificial Intelligence, postgraduate students seeking in-depth knowledge in AI and deep learning, smart computing practitioners, data analysis professionals, and security sector professionals.

About the Author

Chiranji Lal Chowdhary received his Ph.D. in information technology and engineering from VIT; his M.Tech. in computer science and engineering from MSRIT, VTU, Belagavi; and his B.E. in computer science and engineering from MBMEC, JNVU India. He is currently working as an Associate Professor in the SITE, VIT. He has 15 years of experience in academia and 6 months of experience in the industry. He has received research awards for publishing research papers in refereed journals from VIT 5 times consecutively. He has guided more than 20 graduate projects and more than 20 postgraduate level projects. His publications are indexed by the Clarivate Analytics, IEEE, SCOPUS, ACM, and other abstract and citation databases. He is a reviewer for many reputed journals. He is a life member of CSI, ISCA, and ISCA. He has published many papers in refereed journals and has attended international conferences. He has contributed many chapters and is currently in the process of editing books. He has written 3 books and edited 3 books with a reputed publisher. His current research included digital image processing, deep learning, pattern recognition, soft computing, and biometric systems.