| Cryptography and Cryptanalysis Through Computational Intelligence | p. 1 |
| Introduction | p. 2 |
| Block ciphers | p. 2 |
| Public key cryptographic schemes | p. 5 |
| Elliptic Curve based cryptosystems | p. 7 |
| Computational Intelligence Background and Methods | p. 8 |
| Evolutionary Computation | p. 8 |
| Artificial Neural Networks | p. 13 |
| Fuzzy systems | p. 15 |
| Review of Cryptography and Cryptanalysis Through Computational Intelligence | p. 16 |
| Applying Computational Intelligence in Cryptanalysis | p. 18 |
| Cryptanalysis as Discrete Optimization Task | p. 18 |
| Cryptanalysis of Feistel Ciphers through Evolutionary Computation Methods | p. 23 |
| Utilizing Artificial Neural Networks to Address Cryptographic Problems | p. 31 |
| Artificial Neural Networks Applied on Problems Related to Elliptic Curve Cryptography | p. 34 |
| Ridge Polynomial Networks for Cryptography | p. 37 |
| Summary | p. 42 |
| References | p. 43 |
| Multimedia Content Protection Based on Chaotic Neural Networks | p. 51 |
| Introduction | p. 52 |
| Chaotic neural networks' generation and properties | p. 54 |
| Chaotic neural network's generation | p. 54 |
| Chaotic neural network's properties suitable for data encryption | p. 55 |
| Multimedia content encryption based on chaotic neural networks | p. 59 |
| Introduction to multimedia content encryption | p. 59 |
| The cipher based on chaotic neural network | p. 60 |
| Selective video encryption based on Advanced Video Coding | p. 64 |
| Multimedia content authentication based on chaotic neural networks | p. 66 |
| Introduction to multimedia content authentication | p. 66 |
| The hash function based on chaotic neural network | p. 67 |
| The proposed image authentication scheme | p. 69 |
| Performance analysis | p. 70 |
| Future work and discussions | p. 73 |
| Conclusions | p. 74 |
| Acknowledgements | p. 75 |
| References | p. 75 |
| Evolutionary Regular Substitution Boxes | p. 79 |
| Introduction | p. 79 |
| Preliminaries for Substitution Boxes | p. 80 |
| Nash Equilibrium-based Evolutionary Algorithms | p. 82 |
| Evolving Resilient S-Boxes | p. 82 |
| S-Box encoding and genetic operators | p. 83 |
| S-Box evaluation | p. 84 |
| Performance Results | p. 87 |
| Conclusion | p. 88 |
| References | p. 88 |
| Industrial Applications Using Wavelet Packets for Gross Error Detection | p. 89 |
| Introduction | p. 90 |
| Modules | p. 91 |
| Gross Error Types and Examples | p. 93 |
| Problem Specification | p. 95 |
| Mathematical Preliminary | p. 95 |
| Noise Level Detection Problem (NLDP) and Algorithm (NLDA) | p. 97 |
| Some Remarks Regarding Wavelet Based Algorithms | p. 97 |
| Wavelet Based Noise Level Determination | p. 97 |
| Background and State of the Art | p. 98 |
| Noise Level Estimation: State of the Art | p. 99 |
| The Proposed New Procedure for Peak-Noise Level Detection | p. 100 |
| Validation of Peak Noise Level Estimation | p. 103 |
| The Wavelet Algorithm for GEDR | p. 106 |
| Validation and Simulations | p. 109 |
| Outlier Detection Algorithm: MAD Algorithm | p. 110 |
| Results | p. 111 |
| Algorithm Parameterization | p. 114 |
| Experimental Data Sources | p. 116 |
| Dryer, Distillation and Mining Data with Outliers | p. 118 |
| Artificially Contaminated Data and Off-line, On-line Mode | p. 122 |
| Summary, Conclusions and Outlook | p. 125 |
| References | p. 126 |
| Immune-inspired Algorithm for Anomaly Detection | p. 129 |
| Introduction | p. 129 |
| Background | p. 131 |
| The Danger Theory | p. 131 |
| Dendritic Cells as Initiator of Primary Immune Response | p. 133 |
| IDS based on Danger Theory and DCs Properties | p. 136 |
| Properties of DCs for IDS | p. 136 |
| Abstraction of Anomaly Detection Algorithm | p. 138 |
| DCs based Implementation of Practical Applications | p. 141 |
| A Detection of DoM Attack | p. 142 |
| Experiments and Results | p. 145 |
| A Detection of Port Scan Attack | p. 147 |
| Experiments and Results | p. 149 |
| Conclusion | p. 153 |
| References | p. 153 |
| How to Efficiently Process Uncertainty within a Cyberinfrastructure without Sacrificing Privacy and Confidentiality | p. 155 |
| Cyberinfrastructure and Web Services | p. 155 |
| Practical Problem | p. 155 |
| Centralization of Computational Resources | p. 156 |
| Cyberinfrastructure | p. 156 |
| What Is Cyberinfrastructure: The Official NSF Definition | p. 157 |
| Web Services: What They Do - A Brief Summary | p. 157 |
| Processing Uncertainty Within a Cyberinfrastructure | p. 158 |
| Formulation of the problem | p. 158 |
| Description of uncertainty: general formulas | p. 160 |
| Error Estimation for the Results of Data Processing | p. 162 |
| How This Problem Is Solved Now | p. 162 |
| Need for Privacy Makes the Problem More Complex | p. 162 |
| Solution for Statistical Setting: Monte-Carlo Simulations | p. 164 |
| Solution for Interval and Fuzzy Setting | p. 165 |
| Summary | p. 169 |
| References | p. 170 |
| Fingerprint Recognition Using a Hierarchical Approach | p. 175 |
| Introduction | p. 175 |
| Coarse Fingerprint Matching | p. 179 |
| Fingerprint Foreground Segmentation | p. 180 |
| Singular Points Extraction | p. 181 |
| Singular Points Matching | p. 185 |
| Topology-based Fine Matching | p. 185 |
| Delaunay Triangulation of Minutiae Set | p. 188 |
| Modeling Fingerprint Deformation | p. 190 |
| Maximum Bipartite Matching | p. 192 |
| Experimental Results | p. 194 |
| Conclusions | p. 197 |
| References | p. 198 |
| Smart Card Security | p. 201 |
| Introduction | p. 201 |
| Smart Card Specific Attacks | p. 203 |
| Side Channel Attacks | p. 203 |
| Fault Attacks | p. 209 |
| Smart Card Platform Security | p. 214 |
| The Evolution of Smart Card Platforms | p. 214 |
| The Different Multi-application smart card Platforms | p. 215 |
| Java Card | p. 217 |
| Java Card Security | p. 219 |
| GSM and 3G Security | p. 221 |
| 1G - TACS | p. 222 |
| 2G - GSM | p. 222 |
| 3G - UMTS | p. 226 |
| Summary | p. 228 |
| References | p. 229 |
| Governance of Information Security: New Paradigm of Security Management | p. 235 |
| Introduction | p. 236 |
| Rise of the Governance | p. 237 |
| Definitions of the Governance | p. 237 |
| Implications of the Governance | p. 238 |
| Success Factors of the Governance | p. 239 |
| Why the Security Management Fails | p. 240 |
| What the Security Management Can Do | p. 240 |
| What the Security Management Cannot Do | p. 242 |
| Governance of Corporate Security | p. 244 |
| General Frameworks for the Governance | p. 244 |
| Integrated Framework for the Governance of Corporate Security | p. 244 |
| Summary | p. 251 |
| References | p. 252 |
| Author Index | p. 255 |
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