Digital Image Security: Techniques and Applications

Cover
Half Title
Title Page
Copyright Page
Table of Contents
About the editors
List of contributors
Chapter 1: COVID-19 electronic health data security for smart hospitals
1.1 Introduction
1.2 Literature survey
1.3 Preliminary concepts
1.3.1 Non-Subsampled Contourlet Transform (NSCT)
1.3.2 Hessenberg Decomposition (HD)
1.3.3 Multiresolution Singular Value Decomposition (MSVD)
1.4 Proposed method
1.5 Results and analysis
1.6 Conclusion
Acknowledgements
References
Chapter 2: Image security using quantum hash functions
2.1 Introduction
2.2 Classical cryptographic system
2.2.1 Transposition-based algorithm
2.2.2 Value-substitution-based algorithm
2.2.3 Position-substitution-based algorithm
2.3 Quantum computing
2.3.1 Quantum image processing
2.4 Representation of images in quantum computing
2.4.1 Flexible Representation of Quantum Images (FRQI)
2.4.2 Real Ket image format
2.4.3 Qubit lattice format
2.5 Data security in post quantum cryptography
2.6 Image security in post quantum cryptography
2.7 Classical hash functions
2.7.1 Cryptographic hash function
2.8 Quantum hash functions
2.8.1 Generation of QHF
2.9 Quantum key distribution
2.9.1 Types of QKD
2.10 T22 protocol
2.10.1 Two qubit entangled states
2.10.2 Bell states
2.10.3 T22 methodology
2.10.4 Probability of getting the correct measurement
2.11 Conclusion
References
Chapter 3: Post-quantum image security: Challenges and opportunities
3.1 Introduction
3.2 Classical image security
3.2.1 Asymmetric key encryption
3.2.1.1 RSA algorithm
3.2.2 Image security
3.2.3 Discussion and analysis
3.3 Quantum computing primer
3.3.1 Emergence of quantum computing
3.3.2 Quantum mechanics and quantum computing
3.3.2.1 Wave-particle duality
3.3.2.2 Superposition
3.3.2.3 Coherence
3.3.2.4 Entanglement
3.3.2.5 Measurement
3.3.3 Continuous Variable Quantum Computing (CVQC)
3.3.4 Gate-based quantum computing
3.3.4.1 Qubits
3.3.4.2 Bloch sphere representation
3.3.4.3 Measurement
3.3.4.4 Single qubit gates
3.3.4.5 Two qubit gates
3.3.4.6 Multi-qubit gates
3.3.5 Quantum circuit
3.3.6 Quantum teleportation circuit
3.4 Quantum communication
3.5 Security in post-quantum era
3.5.1 Challenges for classical cryptographic methods
3.5.2 Benefits of post-quantum cryptography
3.5.2.1 Intrusion detection
3.5.2.2 Homomorphic cryptography
3.6 A survey of post-quantum cryptography techniques
3.6.1 Quantum key distribution
3.6.2 BB84 protocol
3.6.2.1 Overview
3.6.2.2 Basic principle
3.6.3 Analysis
3.6.4 Lattice-based cryptography
3.6.4.1 Overview
3.6.4.2 Short Integer Solutions (SIS)
3.6.4.3 Image security perspective
3.6.5 Multivariate cryptography
3.6.5.1 Overview
3.6.5.2 Methodology
3.6.5.3 Image security perspective
3.6.6 Hash-based cryptography
3.6.6.1 Overview
3.6.6.2 Methodology
3.6.6.3 Image security perspective
3.6.7 Code-based cryptography
3.6.7.1 Overview
3.6.7.2 Methodology
3.6.7.3 Image security perspective
3.6.8 Supersingular elliptic curve isogeny cryptography
3.6.8.1 Overview
3.6.8.2 Methodology
3.6.8.3 Image security perspective
3.6.9 Symmetric key quantum resistance
3.6.9.1 Overview
3.6.9.2 Image security perspective
3.7 Conclusion
References
Chapter 4: Moving towards 3D-biometric
4.1 Introduction
4.2 3D face biometric
4.2.1 Facial biometric
4.2.2 Ear biometric
4.2.3 Iris biometric
4.2.4 Skull biometric
4.3 3D hand biometric
4.3.1 Fingerprint biometric
4.3.2 Finger vein biometric
4.3.3 Palm biometric
4.4 3D gait biometric
4.5 Conclusion
Acknowledgements
References
Chapter 5: A Secured Dual Image Watermarking technique using QR decomposition, Hénon map, and Chaotic encryption in wavelet domain and its authentication using BRISK
5.1 Introduction
5.2 Preliminaries
5.2.1 Lifting wavelet transform
5.2.2 QR decomposition
5.2.3 Hénon map
5.2.4 Chaotic logistic map
5.3 Watermarking procedure
5.3.1 Embedding process
5.3.2 Extraction process
5.4 Simulation results and discussion
5.5 BRISK features matching
5.6 Comparison of results
5.7 Conclusion
References
Chapter 6: Securing digital images using HT-MSVD in wavelet domain
6.1 Introduction
6.2 Related works
6.3 Proposed watermarking technique
6.3.1 Embedding technique
6.3.2 Extraction technique
6.4 Simulation results
6.5 Conclusions
References
Chapter 7: Scalable edge computing architecture for multimedia data management: Challenges and research avenues
7.1 Introduction to the edge computing ecosystem
7.1.1 Dig into edge computing: drive from cloud computing, wrench from Internet of Things, data consumer to data producer
7.1.2 Contribution and novelty of the work
7.2 Edge computing ecosystem
7.2.1 Edge computing architecture and characteristics
7.2.1.1 General architecture
7.2.1.2 Characteristic features
7.2.2 Edge computing processing archetypes
7.2.3 MEC architecture and characteristics
7.3 Multimedia data processing and management in edge architecture
7.3.1 Why edge processing for multimedia data?
7.3.2 Challenges and requirements for managing multimedia data in edge computing
7.4 Solutions to designing an intelligent edge computing ecosystem for multimedia (MM) data processing and analysis
7.4.1 Applying Machine Learning (ML) and Deep Learning (DL) techniques for MM data analysis
7.4.1.1 Services at edge
7.4.2 Simulation of edge computing with scalable peer-to-peer (P2P) networking
7.4.2.1 Simulation result of edge computing with peer-to-peer (P2P) networking
7.5 Conclusion and future scope
References
Chapter 8: Trustworthiness in deepfake detection using explainability
8.1 Introduction
8.2 Literature survey
8.3 Explainability in deepfake detection
8.3.1 Importance of explainability in deepfake detection
8.3.2 Types and methods of explainability in deepfake detection
8.3.3 Local Interpretable Model-Agnostic Explanations (LIME)
8.4 Methodology
8.4.1 Data pre-processing
8.4.1.1 Dataset
8.4.1.2 Splitting
8.4.1.3 Building a data pipeline
8.4.2 Classification models
8.4.3 Explainability using LIME
8.5 Metrics and experimental setup
8.5.1 Evaluation metric
8.5.2 Experimental setup
8.6 Results and discussion
8.7 Conclusion
References
Chapter 9: Cyber threat intelligence: A standardized protective approach for industrial cyber defense
9.1 Introduction
9.2 CTI life cycle
9.3 Threat intelligence modeling
9.4 Next-generation threats
9.5 Cyber threat intelligence sub-domains
9.6 Fundamental concept of incident response
9.7 Cyber threat intelligence framework for energy cloud environments
9.8 Benefits of CTI
9.9 Challenges of CTI
9.10 Conclusion
References
Chapter 10: Watermarking with blockchain: A survey
10.1 Introduction
10.2 Our contribution
10.3 Classification of BC framework for digital content protection
10.3.1 Types of blockchain systems
10.3.2 Types of transactions
10.3.3 Data automation
10.3.4 Types of cryptocurrencies
10.3.5 Consensus protocols
10.3.6 Content protection mechanism
10.4 Joint watermarking and blockchain-based techniques
10.5 Potential challenges
10.6 Conclusion
References
Chapter 11: No reference medical image quality assessment for image security and authorization
11.1 Introduction
11.2 Proposed methodology
11.2.1 Two-dimensional wavelet decomposition
11.2.2 Wavelet coefficient modeling and feature extraction
11.2.3 Noise variance in diagonal sub-band
11.2.4 Spatial correlation feature extractor
11.2.5 NSS feature extraction in the wavelet domain
11.2.6 SVM regression and parameter selection
11.3 Experimental results
11.4 Conclusion
References
Chapter 12: Do digital images tell the truth?
12.1 Introduction
12.2 Related techniques
12.2.1 Low-level image processing techniques
12.2.2 Machine learning approaches
12.2.2.1 Local descriptor-based techniques
12.2.2.2 Clustering
12.2.3 Deep learning approaches
12.2.4 Datasets
12.2.5 Research challenges
12.3 Discussion
12.4 Conclusion
References
Chapter 13: A multi-layer encryption with AES and Twofish encryption algorithm for smart assistant security
13.1 Introduction
13.2 Literature survey
13.3 Proposed system
13.3.1 Uploading voice
13.3.2 Retrieving voice
13.3.3 Multi-layer feature characterizations
13.3.4 Identity-based encryption
13.3.5 BLAKE2 hash algorithm
13.3.6 Advanced Encryption Standard (AES)
13.3.7 Twofish
13.3.7.1 The function F
13.3.7.2 The function g
13.3.7.3 The key schedule
13.4 Result and discussion
13.4.1 Experimental setup
13.4.2 Assessment criteria
13.4.3 Encryption time
13.4.4 Time-based algorithm for decoding
13.5 Conclusion
References
Chapter 14: Cancelable biometrics for fingerprint template protection
14.1 Introduction
14.2 Cancelable biometrics
14.3 Generation of alignment-free and non-invertible fingerprint template using pair-polar structures of minutiae
14.4 Generation of alignment-free and secure fingerprint template using DFT for consumer electronics devices
14.5 Generation of alignment-free and secure fingerprint template using enhanced fingerprint shell
14.6 Discussion
14.7 Conclusion
References
Chapter 15: Computational intelligence: An optimization perspective for data privacy against adversaries
15.1 Introduction
15.1.1 Importance of medical data security
15.1.2 Security measures of medical data
15.2 Overview of CI
15.2.1 Evolutionary computation
15.3 CI and data security
15.4 Optimal key generation for medical data security
15.4.1 Advantages of EC for key generation
15.4.2 How to implement EC methods for optimal key generation in medical data security?
15.4.3 Limitations of EC approaches
15.5 Future directions
15.6 Conclusion
References
Index