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.
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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.
Dr. Srinath Doss is the Professor and Dean in the Faculty of Engineering and Technology, Botho University, responsible for Botswana, Lesotho, Eswatini, Namibia and Ghana Campuses. He has previously worked with various reputed Engineering colleges in India, and with Garyounis University, Libya. He has written good number of books and more than 80 papers in International Journals and attended several prestigious conferences. His research interests include MANET, Information Security, Network Security and Cryptography, Artificial Intelligence, Cloud Computing and Wireless and Sensor Network. He serves as an editorial member and reviewer for reputed international journals, and an advisory member for various prestigious conference. Prof. Srinath is member of IAENG and Associate Member in UACEE.
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Hardcover. Condizione: new. Hardcover. 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. It is a valuable resource for those looking to incorporate advanced security measures into their products and services. With a focus on practical insights and real-world applications, this book is an essential guide for understanding and implementing steganography and deep learning techniques to enhance security in digital transmission systems. In an era defined by digital connectivity, securing sensitive information against cyber threats is a pressing concern. As transmission systems advance, so do the methods of intrusion and data theft. This book presents a timely solution by integrating steganography, the ancient art of concealing information, with innovative deep learning techniques. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9798369322239
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Buch. Condizione: Neu. Enhancing Steganography Through Deep Learning Approaches | Vijay Kumar (u. a.) | Buch | Englisch | 2024 | IGI Global | EAN 9798369322239 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Codice articolo 130405324
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