Information Hiding and Machine Learning

Ashok Kumar Yadav

ISBN 10: 3346795632 / ISBN 13: 9783346795632

Published by GRIN Verlag, 2023

About this Item

Druck auf Anfrage Neuware - Printed after ordering - Document from the year 2023 in the subject Computer Sciences - Artificial Intelligence, Amity University (Amity School of Engineering and Technology), course: Information Security, Machine Learning, language: English, abstract: Information security is a challenging issue with the high growth rate of the internet. Cryptography, Steganography, and Digital watermarking techniques are widely used for information security for different purposes. In this book, we discuss various methods of hiding information using machine learning techniques.Chapter one is the foundation of the research conducted during the period and dis-cussed in this book. It also overview the problem statement, methodology, objectives, achievements and motivation of the proposed study. It also provides an overview of the organization of this book.In chapter two, the main focus is to review the existing digital image watermarking techniques based on artificial neural network, support vector regression, support vector machines, genetic algorithm and combination of these machine learning algorithms called hybrid techniques based image watermarking. The reviews of these watermarking schemes give the effective solution for copyright protection applications. It is observed that machine learning algorithms are used to reduce the trade-off between robustness and imperceptibility in spatial as well as transform domain. In addition to robustness and imperceptibility, some of the researchers have focused on security of the watermark and how much information is stored in multimedia contents.

Seller Inventory # 9783346795632

Bibliographic Details

• Title: Information Hiding and Machine Learning
• Publisher: GRIN Verlag
• Publication Date: 2023
• Language: English
• ISBN 10: 3346795632
• ISBN 13: 9783346795632
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 210W x 148H x 11D millimeters 210 millimeters width by 148 millimeters height by 11 millimeters depth
• Weight: 230 grams

About this title

Synopsis

Document from the year 2023 in the subject Computer Sciences - Artificial Intelligence, Amity University (Amity School of Engineering and Technology), course: Information Security, Machine Learning, language: English, abstract: Imagine a world where digital content is seamlessly protected, its authenticity verifiable at a glance. This book plunges into the cutting-edge realm of digital watermarking, offering innovative solutions for securing multimedia in an increasingly interconnected world. Dive into the intricacies of image watermarking through the lens of advanced machine learning techniques, specifically Lagrangian Twin Support Vector Regression (LTSVR) and Genetic Algorithms (GA). Explore how these powerful algorithms are harnessed to create robust and imperceptible watermarks, ensuring copyright protection without compromising visual quality. Uncover the secrets of watermark embedding and extraction in both the Discrete Cosine Transform (DCT) and Wavelet Transform (WT) domains, comparing and contrasting the strengths of each approach. Delve into novel methodologies incorporating QR decomposition, further enhancing the efficiency and resilience of watermarking schemes. This book meticulously details the optimization of watermarking systems, balancing the critical factors of robustness against various attacks and imperceptibility to maintain the integrity of the original content. Whether you're a seasoned researcher or a curious newcomer, this exploration of digital watermarking provides a comprehensive understanding of the latest advancements in securing digital assets, paving the way for a future where intellectual property is safeguarded with unparalleled precision and sophistication. Discover how the fusion of machine learning and signal processing is revolutionizing copyright protection in the digital age. Explore practical applications and gain insights into the performance evaluation of digital watermarking schemes. This book is essential reading for any