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Table of Contents
Intro
Preface
Acknowledgements
Editor biographies
Irshad Ahmad Ansari
Varun Bajaj
Contributor biographies
Mahdie Abazar
Parmeshwar Birajadar
Seyed Mostafa FakhrAhmad
Vikram M Gadre
Ali Ghorbani
Jay Gohil
Abdelhamid Helali
Sunil Kumar Jauhar
Ameya Kshirsagar
S Kuppa
Hassen Maaref
V M Manikandan
Suja Cherukullapurath Mana
Peyman Masjedi
Ridha Mghaieth
Amina Msolli
Esmaeil Najafi
Akash S Palde
Jay Patel
D S Raghukumar
Vishal Rajput
Antti Rissanen
Marjo Rissanen
T Saipraba
Sagar G Sangodkar
Manan Shah
Tarun Kumar Sharma
Rishi Sinhal
M Suresha
Niranjan Suthar
Mohammad Taheri
Hanzhou Wu
Chapter 1 Blind image watermarking with efficient dual restoration feature
1.1 Introduction
1.2 Literature review
1.3 Proposed fragile watermarking scheme
1.3.1 Watermark pre-processing
1.3.2 Watermark embedding
1.3.3 Watermark extraction
1.3.4 Self-recovery process
1.4 Experimental results and discussion
1.4.1 Tamper detection anaylsis
1.4.2 Self-recovery of the tampered portion
1.5 Conclusion
Acknowledgements
References
Chapter 2 Secure, robust and imperceptible image watermarking scheme based on sharp frequency localized contourlet transform
2.1 Introduction
2.2 The properties of SFLCT
2.3 The proposed SFLCT watermarking scheme
2.3.1 Computing strength factors
2.4 Implementations and results of the proposed SFLCT scheme
2.4.1 Robustness of the proposed SFLCT scheme
2.4.2 The security examination of the proposed scheme
2.5 Comparative analysis of the proposed scheme
2.6 Conclusion
References
Chapter 3 Content watermarking and data hiding in multimedia security
3.1 Introduction
3.2 Content watermarking in multimedia security
3.2.1 Introduction.
3.2.2 Content watermarking technique reviews
3.2.3 Table pertaining to research work on content watermarking in multimedia security
3.2.4 Inference
3.3 Data hiding in multimedia security
3.3.1 Background
3.3.2 Data hiding technique reviews
3.3.3 Table pertaining to research work on data hiding in multimedia security
3.3.4 Inference
3.4 Conclusion
Acknowledgments
References
Chapter 4 Recent advances in reversible watermarking in an encrypted domain
4.1 Introduction
4.2 Preliminaries
4.2.1 Cover source and formats
4.2.2 Encryption methods
4.2.3 Evaluation metrics
4.2.4 Auxiliary data
4.3 State-of-the-art methods
4.3.1 General framework
4.3.2 Reserving room after encryption
4.3.3 Reserving room before encryption
4.3.4 Challenges and opportunities
4.4 Conclusion
Acknowledgements
References
Chapter 5 An analysis of deep steganography and steganalysis
5.1 Introduction
5.2 Deep learning
5.2.1 Steganalysis
5.2.2 Steganography
5.3 Conclusion
References
Chapter 6 Recent trends in reversible data hiding techniques
6.1 Introduction
6.2 Types of RDH schemes
6.2.1 RDH in natural images
6.2.2 RDH in encrypted images
6.2.3 RDH through encryption (RDHTE)
6.3 Analysis of RDH schemes
6.4 Image dataset for experimental study
6.5 Future scope of the research in RDH
6.6 Conclusion
References
Chapter 7 Anatomized study of security solutions for multimedia: deep learning-enabled authentication, cryptography and information hiding
7.1 Introduction
7.2 Hurdles in conventional approaches for security
7.2.1 Vulnerability due to expansion
7.2.2 Authentication and computational latency
7.2.3 Discrepancy in authentication
7.3 Vulnerability to multimedia content
7.3.1 Data disclosure
7.3.2 Content manipulation.
7.3.3 Link sharing
7.3.4 Steganography
7.3.5 Common workspace
7.4 Analysis of security solutions for multimedia content
7.4.1 Cryptography
7.4.2 Data hiding
7.4.3 Deep learning enabled authentication
7.5 Future scope
7.6 Conclusion
Acknowledgements
References
Chapter 8 New lightweight image encryption algorithm for the Internet of Things and wireless multimedia sensor networks
8.1 Introduction
8.2 Cryptographic primitives
8.2.1 Cryptanalysis
8.2.2 Cryptography system
8.3 Proposed lightweight algorithm
8.4 Safety assessment
8.4.1 Statistical analysis
8.4.2 Sensitivity test: robustness against differential attacks
8.4.3 Calculations speed analysis
8.5 Conclusion
References
Chapter 9 Applying the capabilities of machine learning for multimedia security: an analysis
9.1 Introduction
9.2 Overview of machine learning
9.2.1 Classification
9.2.2 Regression
9.2.3 Deep learning
9.3 Machine learning algorithms for multimedia security
9.4 Advantages of using ML based security mechanism for multimedia
9.5 Conclusion
References
Chapter 10 Assistive communication technology options for elderly care
10.1 Introduction
10.2 Cameras for patient monitoring in hospitals
10.2.1 Cameras for patient supervising in elderly care
10.2.2 Extending camera monitoring from the hospital to the home
10.2.3 Home-access video service as experienced by family members
10.2.4 Home-access video service as experienced by staff
10.2.5 New contexts and possibilities for camera surveillance in elderly care
10.3 Home-access monitoring and security
10.4 Benefits of the service
10.4.1 Benefit for the hospital patient
10.4.2 Benefit to the patient's relatives
10.4.3 Benefit to the organization
10.5 Requirements for the service model.
10.5.1 When is a home-access camera a facet of quality?
10.5.2 Conditions for practice
10.6 Security issues in networked health infrastructure
10.6.1 Information security at the strategic level
10.6.2 Different layers of security
10.6.3 Key elements of safe IT infrastructure in healthcare in the future
10.7 Deploying novel surveillance services in healthcare
10.7.1 Underlining the basics
10.7.2 Design cycles and relevant frames for design
10.7.3 Shared leadership
10.7.4 Challenges of innovation adaptation
10.7.5 New service models and translational design challenges
10.8 Conclusion
References
Chapter 11 Deep learning approach for scenario-based abnormality detection
11.1 Introduction
11.2 Literature study
11.3 Scenario understanding
11.3.1 Key frame extraction using instance segmentation
11.3.2 State full artifacts modelling
11.3.3 Action recognition and attention of key action
11.3.4 A hybrid model for spatio-temporal features
11.3.5 Classification and captioning
11.4 Abnormality detection
11.4.1 Natural abnormality translation
11.5 Datasets
11.6 Challenges
11.7 Trends and strengths
11.8 Conclusion
References
Chapter 12 Ear recognition for multimedia security
12.1 Introduction
12.1.1 Components of a biometric system
12.1.2 Modes of operation
12.1.3 Performance evaluation metrics
12.2 Ear recognition
12.3 Ear detection
12.4 Ear feature extraction
12.4.1 Multiresolution technique for feature extraction
12.4.2 Deep learning technique for feature extraction
12.4.3 Identification and verification experiments
12.5 Conclusion
Acknowledgements
References
Chapter 13 Secure multimedia management: currents trends and future avenues
13.1 Introduction
13.2 Data collection and screening
13.3 Results.
13.3.1 General performance of selected publications
13.3.2 Performance of countries, institutions, and authors
13.3.3 Performance of journals, citations, and keywords
13.3.4 Factorial analysis
13.3.5 Co-citation network
13.3.6 Collaboration worldwide
13.4 Conclusion
References.
Preface
Acknowledgements
Editor biographies
Irshad Ahmad Ansari
Varun Bajaj
Contributor biographies
Mahdie Abazar
Parmeshwar Birajadar
Seyed Mostafa FakhrAhmad
Vikram M Gadre
Ali Ghorbani
Jay Gohil
Abdelhamid Helali
Sunil Kumar Jauhar
Ameya Kshirsagar
S Kuppa
Hassen Maaref
V M Manikandan
Suja Cherukullapurath Mana
Peyman Masjedi
Ridha Mghaieth
Amina Msolli
Esmaeil Najafi
Akash S Palde
Jay Patel
D S Raghukumar
Vishal Rajput
Antti Rissanen
Marjo Rissanen
T Saipraba
Sagar G Sangodkar
Manan Shah
Tarun Kumar Sharma
Rishi Sinhal
M Suresha
Niranjan Suthar
Mohammad Taheri
Hanzhou Wu
Chapter 1 Blind image watermarking with efficient dual restoration feature
1.1 Introduction
1.2 Literature review
1.3 Proposed fragile watermarking scheme
1.3.1 Watermark pre-processing
1.3.2 Watermark embedding
1.3.3 Watermark extraction
1.3.4 Self-recovery process
1.4 Experimental results and discussion
1.4.1 Tamper detection anaylsis
1.4.2 Self-recovery of the tampered portion
1.5 Conclusion
Acknowledgements
References
Chapter 2 Secure, robust and imperceptible image watermarking scheme based on sharp frequency localized contourlet transform
2.1 Introduction
2.2 The properties of SFLCT
2.3 The proposed SFLCT watermarking scheme
2.3.1 Computing strength factors
2.4 Implementations and results of the proposed SFLCT scheme
2.4.1 Robustness of the proposed SFLCT scheme
2.4.2 The security examination of the proposed scheme
2.5 Comparative analysis of the proposed scheme
2.6 Conclusion
References
Chapter 3 Content watermarking and data hiding in multimedia security
3.1 Introduction
3.2 Content watermarking in multimedia security
3.2.1 Introduction.
3.2.2 Content watermarking technique reviews
3.2.3 Table pertaining to research work on content watermarking in multimedia security
3.2.4 Inference
3.3 Data hiding in multimedia security
3.3.1 Background
3.3.2 Data hiding technique reviews
3.3.3 Table pertaining to research work on data hiding in multimedia security
3.3.4 Inference
3.4 Conclusion
Acknowledgments
References
Chapter 4 Recent advances in reversible watermarking in an encrypted domain
4.1 Introduction
4.2 Preliminaries
4.2.1 Cover source and formats
4.2.2 Encryption methods
4.2.3 Evaluation metrics
4.2.4 Auxiliary data
4.3 State-of-the-art methods
4.3.1 General framework
4.3.2 Reserving room after encryption
4.3.3 Reserving room before encryption
4.3.4 Challenges and opportunities
4.4 Conclusion
Acknowledgements
References
Chapter 5 An analysis of deep steganography and steganalysis
5.1 Introduction
5.2 Deep learning
5.2.1 Steganalysis
5.2.2 Steganography
5.3 Conclusion
References
Chapter 6 Recent trends in reversible data hiding techniques
6.1 Introduction
6.2 Types of RDH schemes
6.2.1 RDH in natural images
6.2.2 RDH in encrypted images
6.2.3 RDH through encryption (RDHTE)
6.3 Analysis of RDH schemes
6.4 Image dataset for experimental study
6.5 Future scope of the research in RDH
6.6 Conclusion
References
Chapter 7 Anatomized study of security solutions for multimedia: deep learning-enabled authentication, cryptography and information hiding
7.1 Introduction
7.2 Hurdles in conventional approaches for security
7.2.1 Vulnerability due to expansion
7.2.2 Authentication and computational latency
7.2.3 Discrepancy in authentication
7.3 Vulnerability to multimedia content
7.3.1 Data disclosure
7.3.2 Content manipulation.
7.3.3 Link sharing
7.3.4 Steganography
7.3.5 Common workspace
7.4 Analysis of security solutions for multimedia content
7.4.1 Cryptography
7.4.2 Data hiding
7.4.3 Deep learning enabled authentication
7.5 Future scope
7.6 Conclusion
Acknowledgements
References
Chapter 8 New lightweight image encryption algorithm for the Internet of Things and wireless multimedia sensor networks
8.1 Introduction
8.2 Cryptographic primitives
8.2.1 Cryptanalysis
8.2.2 Cryptography system
8.3 Proposed lightweight algorithm
8.4 Safety assessment
8.4.1 Statistical analysis
8.4.2 Sensitivity test: robustness against differential attacks
8.4.3 Calculations speed analysis
8.5 Conclusion
References
Chapter 9 Applying the capabilities of machine learning for multimedia security: an analysis
9.1 Introduction
9.2 Overview of machine learning
9.2.1 Classification
9.2.2 Regression
9.2.3 Deep learning
9.3 Machine learning algorithms for multimedia security
9.4 Advantages of using ML based security mechanism for multimedia
9.5 Conclusion
References
Chapter 10 Assistive communication technology options for elderly care
10.1 Introduction
10.2 Cameras for patient monitoring in hospitals
10.2.1 Cameras for patient supervising in elderly care
10.2.2 Extending camera monitoring from the hospital to the home
10.2.3 Home-access video service as experienced by family members
10.2.4 Home-access video service as experienced by staff
10.2.5 New contexts and possibilities for camera surveillance in elderly care
10.3 Home-access monitoring and security
10.4 Benefits of the service
10.4.1 Benefit for the hospital patient
10.4.2 Benefit to the patient's relatives
10.4.3 Benefit to the organization
10.5 Requirements for the service model.
10.5.1 When is a home-access camera a facet of quality?
10.5.2 Conditions for practice
10.6 Security issues in networked health infrastructure
10.6.1 Information security at the strategic level
10.6.2 Different layers of security
10.6.3 Key elements of safe IT infrastructure in healthcare in the future
10.7 Deploying novel surveillance services in healthcare
10.7.1 Underlining the basics
10.7.2 Design cycles and relevant frames for design
10.7.3 Shared leadership
10.7.4 Challenges of innovation adaptation
10.7.5 New service models and translational design challenges
10.8 Conclusion
References
Chapter 11 Deep learning approach for scenario-based abnormality detection
11.1 Introduction
11.2 Literature study
11.3 Scenario understanding
11.3.1 Key frame extraction using instance segmentation
11.3.2 State full artifacts modelling
11.3.3 Action recognition and attention of key action
11.3.4 A hybrid model for spatio-temporal features
11.3.5 Classification and captioning
11.4 Abnormality detection
11.4.1 Natural abnormality translation
11.5 Datasets
11.6 Challenges
11.7 Trends and strengths
11.8 Conclusion
References
Chapter 12 Ear recognition for multimedia security
12.1 Introduction
12.1.1 Components of a biometric system
12.1.2 Modes of operation
12.1.3 Performance evaluation metrics
12.2 Ear recognition
12.3 Ear detection
12.4 Ear feature extraction
12.4.1 Multiresolution technique for feature extraction
12.4.2 Deep learning technique for feature extraction
12.4.3 Identification and verification experiments
12.5 Conclusion
Acknowledgements
References
Chapter 13 Secure multimedia management: currents trends and future avenues
13.1 Introduction
13.2 Data collection and screening
13.3 Results.
13.3.1 General performance of selected publications
13.3.2 Performance of countries, institutions, and authors
13.3.3 Performance of journals, citations, and keywords
13.3.4 Factorial analysis
13.3.5 Co-citation network
13.3.6 Collaboration worldwide
13.4 Conclusion
References.