Some error occured while loading the Quick View. Please close the Quick View and try reloading the page.
Modern internet-enabled devices and fast communication technologies have ushered in a revolution in sharing of digital images and video. This may be for social reasons or for commercial and industrial applications, where the data is more likely to include sensitive personal or confidential information. In any event, the shared imagery is intended only for the end-user. Attackers can steal this data or manipulate it for their own uses, causing financial and emotional damage to the owners. Many applications generate important information in the form of images and video, where efficient security is critical. This drives the need for advanced security solutions and the need to continuously develop and maintain security measures in an ever-evolving battle against fraud and malicious intent.
There are various techniques employed in protecting digital media and information, such as digital watermarking, cryptography, stenography, data encryption, etc., In addition, sharing platforms and connected nodes themselves may be open to vulnerabilities and can suffer from security breaches. This book reviews present state-of-the-art research related to the security of digital imagery and video, including developments in machine learning applications. It is particularly suited for those that bridge the academic world and industry, and allows readers to understand the security concerns in the multimedia domain by reviewing present and evolving security solutions, their limitations, and future research directions.
Key Features
- Latest trends in the multimedia security domain
- Includes Machine Learning for multimedia security
- Insight to different security concerns (attacks)
- Reviews present challenges & future opportunities
- Potential & promising solution to the security concerns
Ch 1: This work was supported by Faculty Initiation Grant of PDPM Indian Institute of Information Technology Design and Manufacturing Jabalpur, India.
Ch 3: The authors are grateful to Department of Information and Communication Technology and Department of Chemical Engineering, School of Technology, Pandit Deendayal Petroleum University for the permission to publish this research.
Ch 4: This work was partly supported by the National Natural Science Foundation of China (NSFC) under grant number 61902235, and also supported by the Shanghai “Chenguang” Project under grant number 19CG46.
Ch 7: The authors are grateful to Symbiosis Institute of Technology and Department of Chemical Engineering, School of Technology, Pandit Deendayal Petroleum University for the permission to publish this research.
Ch 12: We would like to thank National Center of Excellence in Technology for Internal Security (NCETIS, IIT Bombay) for providing all the necessary hardware and software resources which helped us to perform all the experiments efficiently. We also like to thank the creators of all the publicly available datasets used in this work. We are grateful to all the IIT Bombay people who actively participated in creating the IIT Bombay ear dataset.
Preface
1 Blind Image Watermarking with Efficient Dual Restoration Feature
2 Secure, Robust and Imperceptible Image Watermarking Scheme Based On SFLCT
3 Content Watermarking and Data Hiding in Multimedia Security
4 Recent Advances in Reversible Watermarking in Encrypted Domain
5 A Review of Deep Steganography and Steganalysis
6 Recent Trends in Reversible Data Hiding Techniques
7 Anatomized Study of Security Solutions for Multimedia Deep Learning-Enabled Authentication, Cryptography and Information Hiding
8 New Lightweight Image Encryption Algorithm for The Internet of Things and Wireless Multimedia Sensor Networks
9 Applying the Capabilities of Machine Learning for Multimedia Security and Analysis
10 Assistive Communication Technology Options for Elderly Care
11 Deep Learning Approach for Scenario-Based Abnormality Detection
12 Ear Recognition for Multimedia Security
13 Secure Multimedia Management Currents Trends and Future Avenues