Coding theory and cryptology Books

Book SynopsisThis book constitutes the refereed proceedings of the 4th International Conference on Sequences and Their Applications, SETA 2006. The book presents 32 revised full papers together with 4 invited lectures. The papers are organized in topical sections on linear complexity of sequences, correlation of sequences, stream ciphers and transforms, topics in complexities of sequences, multi-sequence synthesis, sequences and combinatorics, FCSR sequences, aperiodic correlation and applications, and boolean functions, and more.Table of ContentsInvited Papers.- Shift Register Sequences – A Retrospective Account.- The Probabilistic Theory of the Joint Linear Complexity of Multisequences.- Multi-Continued Fraction Algorithms and Their Applications to Sequences.- Codes for Optical CDMA.- Linear Complexity of Sequences.- On the Linear Complexity of Sidel’nikov Sequences over .- Linear Complexity over F p of Ternary Sidel’nikov Sequences.- Bounds on the Linear Complexity and the 1-Error Linear Complexity over F p of M-ary Sidel’nikov Sequences.- The Characterization of 2 n -Periodic Binary Sequences with Fixed 1-Error Linear Complexity.- Correlation of Sequences.- Crosscorrelation Properties of Binary Sequences with Ideal Two-Level Autocorrelation.- Extended Hadamard Equivalence.- Analysis of Designing Interleaved ZCZ Sequence Families.- Stream Ciphers and Transforms.- Security of Jump Controlled Sequence Generators for Stream Ciphers.- Improved Rijndael-Like S-Box and Its Transform Domain Analysis.- Topics in Complexities of Sequences.- Nonlinear Complexity of Binary Sequences and Connections with Lempel-Ziv Compression.- On Lempel-Ziv Complexity of Sequences.- Computing the k-Error N-Adic Complexity of a Sequence of Period p n .- On the Expected Value of the Joint 2-Adic Complexity of Periodic Binary Multisequences.- Linear/Nonlinear Feedback Shift Register Sequences.- On the Classification of Periodic Binary Sequences into Nonlinear Complexity Classes.- Sequences of Period 2 N –2.- A New Algorithm to Compute Remote Terms in Special Types of Characteristic Sequences.- Multi-sequence Synthesis.- Implementation of Multi-continued Fraction Algorithm and Application to Multi-sequence Linear Synthesis.- The Hausdorff Dimension of the Set of r-Perfect M-Multisequences.- Filtering Sequences and Pseudorandom Sequence Generators.- Lower Bounds on Sequence Complexity Via Generalised Vandermonde Determinants.- Construction of Pseudo-random Binary Sequences from Elliptic Curves by Using Discrete Logarithm.- On the Discrepancy and Linear Complexity of Some Counter-Dependent Recurrence Sequences.- Sequences and Combinatorics.- Nonexistence of a Kind of Generalized Perfect Binary Array.- FCSR Sequences.- On the Distinctness of Decimations of Generalized l-Sequences.- On FCSR Memory Sequences.- Periodicity and Distribution Properties of Combined FCSR Sequences.- Aperiodic Correlation and Applications.- Generalized Bounds on Partial Aperiodic Correlation of Complex Roots of Unity Sequences.- Chip-Asynchronous Version of Welch Bound: Gaussian Pulse Improves BER Performance.- Boolean Functions.- On Immunity Profile of Boolean Functions.- Reducing the Number of Homogeneous Linear Equations in Finding Annihilators.- The Algebraic Normal Form, Linear Complexity and k-Error Linear Complexity of Single-Cycle T-Function.- Partially Perfect Nonlinear Functions and a Construction of Cryptographic Boolean Functions.- Construction of 1-Resilient Boolean Functions with Very Good Nonlinearity.

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Book SynopsisDigitale Kommunikation dringt in immer mehr Bereiche privater und unternehmerischer Anwendungsfelder ein. Seit 1997 sind die gesetzlichen Rahmenbedingungen in Deutschland für rechtlich gesicherte Vorgänge im Internet geschaffen. Zentraler Bestandteil ist die digitale Signatur. Die Autoren erklären anschaulich und detailliert deren Konzept und Einsatzmöglichkeiten. Die Funktionen von Signatur, Trustcenter, Chipkarte und asymmetrischem Schlüsselverfahren werden dargestellt und durch zahlreiche Diagramme verdeutlicht. Die Informationen dienen als Entscheidungsgrundlage für den Einsatz der digitalen Signatur in Firmen, Institutionen und Behörden. Die Anwendungsbeispiele beziehen sich auf Business-to-Business- und Business-to-Customer-Beziehungen in Intranet und Internet. Das Werk wendet sich vor allem an Produzenten digitaler Medien sowie Entscheider in Wirtschaft und Verwaltung.Table of ContentsAusgangslage.- Konzept.- Zielsetzung.- Das Prinzip der digitalen Signatur.- Rechtliche Aspekte.- Europäische Entwicklung.- Internationale Entwicklungen.- Einsatzfelder.- Business-to-Business-Kommunikation.- Business-to-Customer-Kommunikation.- Intranet (firmeninterne Kommunikation).- Behördliche Kommunikation.- Gesetzesgrundlage.- Glossar.- Literaturverzeichnis.- Index.

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Book SynopsisAdvances Primitives.- homomorphic encryption.- digital signatures.

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Book Synopsisdigital signatures.- public-key cryptography.- pairing-based cryptography.

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Book Synopsispairing-based cryptography, threshold cryptography.- isogeny-based cryptography.- post-quantum cryptography.

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Book Synopsispost-quantum cryptography.- secure data structures.- lattice-based cryptography.- lattice assumptions.

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Book SynopsisKey Exchange Protocols.- Succinct Arguments.- Verifiable Computation.- Zero-knowledge Protocols.

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Book SynopsisCryptanalyasis on Pubilc-Key Schemes.- Fault Attacks and Side-Channel Analysis.- Cryptanalysis on Various Problems.- Quantum Cryptanalysis.

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Book Synopsis.- Multi-Party Computation..- SecFloatPlus: More Accurate Floating-Point Meets Secure Two-Party Computation..- Consecutive Adaptor Signature Scheme: From Two-Party to N-Party Settings..- Secure Five-party Computation with Private Robustness and Minimal Online Communication..- Model Extraction Attack on MPC Hardened Vertical Federated Learning..- Searchable Encryption..- Verifiable Conjunctive Searchable Symmetric Encryption with Result Pattern Hiding..- Compressed Cookies: Practical Wildcard Symmetric Searchable Encryption with Optimized Storage..- Encryption..- PPA-DCA: A Privacy-Preserving and Accountable Data Collection and Analysis Scheme Using Decentralized Multi-Client Functional Encryption..- Ideal Public Key Encryption, Revisited..- Simple Construction of PEKS from LWE-based IBE in the Standard Model..- Signature..- Traceable Ring Signatures: Logarithmic-Size, Without Any Setup, from Standard Assumptions..- Tightly Secure Identity-based Signature from Cryptographic Group Actions..- Generic Construction of Withdrawable Signature from Hash-ThenOne-Way Signature..- Efficient Fork-Free BLS Multi-Signature Scheme with Incremental Signing..- Threshold Ring Signatures: From DualRing to the t+1 Rings..- Lattice-Based Non-Interactive Blind Signature Schemes in the Random Oracle Model.

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Book SynopsisChapter 1. Introduction.-Chapter 2. Semantic Communication System And Synonymous Mapping.-Chapter 3. Semantic Entropy.-Chapter 4. Semantic Relative Entropy And Mutual Information.-Chapter 5. Semantic Channel Capacity And Semantic Rate Distortion.-Chapter 6. Semantic Lossless Source Coding.-Chapter 7. Semantic Channel Coding.-Chapter 8. Semantic Lossy Source Coding.-Chapter 9. Semantic Information Measure Of Continuous Message.-Chapter 10. Semantic Joint Source Channel Coding.- Chapter 11 Conclusion.

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Book Synopsis.- Chapter 1 Introduction to Image and Video Coding.- 1.1 Basic Concept of Image and Video Data.- 1.2 Representative Image and Video Datasets.- 1.3 AI-based Compression Requirement for Image and Video.- 1.4 Image and Video Coding Performance Evaluation.- 1.5 Organization of This Book.- 1.6 Summary.- Chapter 2 Fundamentals for Deep Learning-based Image and Video Coding.- 2.1 Introduction.- 2.2 Fundamental Knowledge of Deep Learning.- 2.3 Autoencoder and Variational Autoencoder.- 2.4 Principles and Framework of Deep Learning-based Image and Video Coding.- 2.5 Summary.- Chapter 3 Image and Video Quality Assessment and Perception Models.- 3.1 Introduction.- 3.2 Quality Assessment of Image and Video.- 3.3 Just Noticeable Distortion of Image and Video.- 3.4 Visual Attention Modeling of Image and Video.- 3.5 Comparative Analysis.- 3.6 Summary.- Chapter 4 Deep Learning-based Image Coding.- 4.1 Introduction.- 4.2 Representative Methods of Lossless Image Coding.- 4.3 Representative Methods of Lossy Image Coding.- 4.4 Comparative Analysis.- 4.5 Summary.- Chapter 5 Deep Learning-based Video Coding.- 5.1 Introduction.- 5.2 Framework and Key Components.- 5.3 Representative Methods of Video Coding.- 5.4 Comparative Analysis.- 5.5 Summary.- Chapter 6 Deep Learning-based 3D and Multimodal Coding.- 6.1 Introduction.- 6.2 Overall Framework and Datasets.- 6.3 Representative Methods of 3D and Multimodal Coding.- 6.4 Comparative Analysis.- 6.5 Summary.- Chapter 7 Human and Machine Vision-Oriented Image and Video Coding.- 7.1 Introduction.- 7.2 Representative Methods of Human Perception-based Coding.- 7.3 Representative Methods of Machine Perception-based Coding.- 7.4 Comparative Analysis.- 7.5 Summary.- Chapter 8 Compression Artifacts Removal for Image and Video Coding.- 8.1 Introduction.- 8.2 Representative Methods of Compressed Image Artifacts Reduction.- 8.3 Representative Methods of Compressed Video Artifacts Reduction.- 8.4 Comparative Analysis.- 8.5 Summary.- Chapter 9 Deep Learning-based Image and Video Coding Standards.- 9.1 Introduction.- 9.2 Overview of International Standards.- 9.3 IEEE AI-based Image and Video Coding Standard.- 9.4 JPEG AI-based Image and Video Coding Standard.- 9.5 MPEG Video Coding for Machines Standard.- 9.6 MPAI End-to-End Video Coding Standard.- 9.7 Comparative Analysis.- 9.8 Summary.- Chapter 10 Implementations for Deep Learning-based Image and Video Coding.- 10.1 Introduction.- 10.2 Basics of Neural Network Compression.- 10.3 Software and Hardware Platforms for Acceleration.- 10.4 Lightweight Methods for Deep Compression Network.- 10.5 Comparative Analysis.- 10.6 Summary.- Chapter 11 Open Source Projects for Deep Learning-based Image and Video Coding.- 11.1 Introduction.- 11.2 Representative Open Source Projects for Image Coding.- 11.3 Representative Open Source Projects for Video Coding.- 11.4 Comparative Analysis.- 11.5 Summary.- Chapter 12 Future Works for AI-based Image and Video Coding.- 12.1 Future Work on Quality Assessment and Perception Models for Image and Video.- 12.2 Future Work on Deep Learning-based for Image Coding.- 12.3 Future Work on Deep Learning-based for Video Coding.- 12.4 Future Work on Deep Learning-based for 3D and Multimodal Coding.- 12.5 Future Work on Human and Machine Vision Oriented Image and Video Coding.- 12.6 Future Work on Compression Artifacts Removal for Image and Video Coding.- 12.7 Future Work on Deep Learning-based Image and Video Coding Standards.- 12.8 Future Work on Implementations for Deep Learning-based Image and Video Coding.- 12.9 Future Work on Open Source Projects for Deep Learning-based Image and Video Coding.

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Book Synopsis.- Chapter1. Introduction..- Chapter 2. Background Knowledge..- Chapter 3. Predictive Coding..- Chapter 4. Transform Coding..- Chapter 5. Quantization Techniques..- Chapter 6. Entropy Coding..- Chapter 7. MPEG Geometry-based Point Cloud Compression (G-PCC) Standard..- Chapter 8. AVS Point Cloud Compression Standard..- Chapter 9. MPEG Video-based Point Cloud Compression (V-PCC) Standard..- Chapter 10. MPEG AI-based 3D Graphics Coding Standard..- Chapter 11. Future Work..- Index.

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