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5G networks : fundamental requirements, enabling technologies, and operations management / / Anwer Al-Dulaimi, Xianbin Wang, and Chih-Lin I
| 5G networks : fundamental requirements, enabling technologies, and operations management / / Anwer Al-Dulaimi, Xianbin Wang, and Chih-Lin I |
| Autore | Al-Dulaimi Anwer <1974-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley-IEEE, , 2018 |
| Descrizione fisica | 1 online resource (787 pages) |
| Disciplina | 621.38456 |
| Soggetto topico |
Wireless communication systems
Global system for mobile communications Mobile communication systems |
| ISBN |
1-119-33394-6
1-119-33314-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Foreword xxi Preface xxv Author Bios xxvii List of Contributors xxxi List of Abbreviations xxxvii Introduction 1 Part I Physical Layer for 5G Radio Interface Technologies 13 1 Emerging Technologies in Software, Hardware, and Management Aspects Toward the 5G Era: Trends and Challenges 15; Ioannis-Prodromos Belikaidis, Andreas Georgakopoulos, Evangelos Kosmatos, Stavroula Vassaki, Orestis-Andreas Liakopoulos, Vassilis Foteinos, Panagiotis Vlacheas, and Panagiotis Demestichas 1.1 Introduction 15 1.2 5G Requirements and Technology Trends 17 1.3 Status and Challenges in Hardware and Software Development 20 1.4 5G Network Management Aspects Enhanced with Machine Learning 38 1.5 Conclusion 45 References 45 2 Waveform Design for 5G and Beyond 51; Ali Fatih Demir, Mohamed Elkourdi, Mostafa Ibrahim,
And Huseyin Arslan 2.1 Introduction 51 2.2 Fundamentals of the 5G Waveform Design 52 2.3 Major Waveform Candidates for 5G and Beyond 58 2.4 Summary 70 2.5 Conclusions 73 References 73 3 Full-Duplex System Design for 5G Access 77; Shu-ping Yeh, Jingwen Bai, PingWang, Feng Xue, Yang-seok Choi, Shilpa Talwar, Sung-en Chiu, and Vinod Kristem 3.1 Introduction 77 3.2 Self-Interference Cancellation 79 3.3 FD System Design: Opportunities and Challenges 82 3.4 Designing the FD System 84 3.5 System-Level Performance Analysis 108 3.6 Conclusions and Future Directions 125 References 130 4 Nonorthogonal Multiple Access for 5G 135 ; Linglong Dai, Bichai Wang, Ruicheng Jiao, Zhiguo Ding, Shuangfeng Han, And Chih-Lin I 4.1 Introduction 135 4.2 Basic Principles and Advantages of NOMA 137 4.3 Power-Domain NOMA 142 4.4 Code-Domain NOMA 155 4.5 Other NOMA Schemes 170 4.6 Comparison and Trade-Off Analysis of NOMA Solutions 178 4.7 Performance Evaluations and Transmission Experiments of NOMA 181 4.8 Opportunities and Future Research Trends 185 4.9 Conclusions 189 References 189 5 Code Design for Multiuser MIMO 205 ; Guanghui Song, Yuhao Chi, Kui Cai, Ying Li, and Jun Cheng 5.1 Introduction 206 5.2 Multiuser Repetition-Aided IRA Coding Scheme 207 5.3 Iterative Decoding and EXIT Analysis 209 5.4 Code Optimization Procedure 217 5.5 Numerical Results and Comparisons 218 5.6 Conclusion 230 References 231 6 Physical Layer Techniques for 5G Wireless Security 237 ; Batu K -- Chalise, Himal A. Suraweera, Gan Zheng, and Risto Wichman 6.1 Introduction 237 6.2 5G Physical Layer Architecture 241 6.3 Secure Full-Duplex Receiver Jamming 247 6.4 Secure Full-Duplex Bidirectional Communications 255 6.5 Secure Full-Duplex Relay Communications 259 6.6 Future Directions and Open Issues 266 6.7 Conclusion 268 References 269 7 Codebook-Based Beamforming Protocols for 5G Millimeter Wave Communications 275; Anggrit Dewangkara Yudha Pinangkis, Kishor Chandra, and R. Venkatesha Prasad 7.1 Introduction 275 7.2 Beamforming Architecture 278 7.3 Beam Searching Algorithm 280 7.4 Codebook Design 286 7.5 Beamforming Evaluation 290 7.6 Conclusion 291 References 293 Part II Radio Access Technology for 5G Networks 299 8 Universal Access in 5G Networks: Potential Challenges and Opportunities for Urban and Rural Environments 301; Syed Ali Hassan, Muhammad Shahmeer Omar, Muhammad Ali Imran, Junaid Qadir, and Dushantha Nalin K. Jayakody 8.1 Introduction 301 8.2 Access for Urban Environments 302 8.3 Providing Access to Rural Areas 312 8.4 Conclusions 320 References 321 9 Network Slicing for 5G Networks 327; Xavier Costa-Pérez, Andrés Garcia-Saavedra, Fabio Giust, Vincenzo Sciancalepore, Xi Li, Zarrar Yousaf, And Marco Liebsch 9.1 Introduction 327 9.2 End-to-End Network Slicing 328 9.3 Network Slicing MANO 334 9.4 Network Slicing at the Mobile Edge 343 9.5 Network Slicing at the Mobile Transport 349 9.6 Network Slicing at the Mobile Cloud 358 9.7 Acknowledgment 364 References 365 10 The Evolution Toward Ethernet-Based Converged 5G RAN 371; Jouni Korhonen 10.1 Introduction to RAN Transport Network 372 10.2 Evolving RAN Toward 5G Requirements 384 10.3 Ethernet-Based 5G RAN 399 10.4 Summary 418 References 418 11 Energy-Efficient 5G Networks Using Joint Energy Harvesting and Scheduling 427; Ahmad Alsharoa, Abdulkadir Celik, and Ahmed E. And Complementarity 519; Renaud Di Francesco and Peter Karlsson 14.1 Overview 519 14.2 Introduction 520 14.3 Demand Analysis 522 14.4 Reviewing the Standardization Path So Far 532 14.5 Conclusion on Machine-Type 5G 537 References 538 Part IV Vertical 5G Applications 543 15 Social-Aware Content Delivery in Device-to-Device Underlay Networks 545; Chen Xu, Caixia Gao, Zhenyu Zhou, ShahidMumtaz, and Jonathan Rodriguez 15.1 Introduction 545 15.2 Related Works 548 15.3 System Model 552 15.4 Problem Formulation 557 15.5 Social Network-Based Content Delivery Matching Algorithm for D2D Underlay Networks 558 15.6 Numerical Results 565 15.7 Conclusions 569 References 570 16 Service-Oriented Architecture for IoT Home Area Networking in 5G 577; Mohd Rozaini Abd Rahim, Rozeha A -- Rashid, AhmadM. |
| Record Nr. | UNINA-9910555106403321 |
Al-Dulaimi Anwer <1974->
|
||
| Hoboken, New Jersey : , : Wiley-IEEE, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Adaptive signal processing : next generation solutions / / [edited by] Tulay Adali, Simon S. Haykin
| Adaptive signal processing : next generation solutions / / [edited by] Tulay Adali, Simon S. Haykin |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-IEEE, c2010 |
| Descrizione fisica | 1 online resource (428 p.) |
| Disciplina | 621.382/2 |
| Altri autori (Persone) |
AdaliTulay
HaykinSimon S. <1931-> |
| Collana | Adaptive and learning systems for signal processing, communications and control series |
| Soggetto topico | Adaptive signal processing |
| ISBN |
1-282-65650-3
9786612656507 0-470-57575-1 0-470-57574-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Preface -- Contributors -- Chapter 1 Complex-Valued Adaptive Signal Processing -- 1.1 Introduction -- -- 1.2 Preliminaries -- 1.3 Optimization in the Complex Domain -- 1.4 Widely Linear Adaptive Filtering -- 1.5 Nonlinear Adaptive Filtering with Multilayer Perceptrons -- 1.6 Complex Independent Component Analysis -- 1.7 Summary -- 1.8 Acknowledgment -- 1.9 Problems -- References -- Chapter 2 Robust Estimation Techniques for Complex-Valued Random Vectors -- 2.1 Introduction -- 2.2 Statistical Characterization of Complex Random Vectors -- 2.3 Complex Elliptically Symmetric (CES) Distributions -- 2.4 Tools to Compare Estimators -- 2.5 Scatter and Pseudo-Scatter Matrices -- 2.6 Array Processing Examples -- 2.7 MVDR Beamformers Based on M-Estimators -- 2.8 Robust ICA -- 2.9 Conclusion -- 2.10 Problems -- References -- Chapter 3 Turbo Equalization -- 3.1 Introduction -- 3.2 Context -- 3.3 Communication Chain -- 3.4 Turbo Decoder: Overview -- 3.5 Forward-Backward Algorithm -- 3.6 Simplified Algorithm: Interference Canceler -- 3.7 Capacity Analysis -- 3.8 Blind Turbo Equalization -- 3.9 Convergence -- 3.10 Multichannel and Multiuser Settings -- 3.11 Concluding Remarks -- 3.12 Problems -- References -- Chapter 4 Subspace Tracking for Signal Processing -- 4.1 Introduction -- 4.2 Linear Algebra Review -- 4.3 Observation Model and Problem Statement -- 4.4 Preliminary Example: Oja's Neuron -- 4.5 Subspace Tracking -- 4.6 Eigenvectors Tracking -- 4.7 Convergence and Performance Analysis Issues -- 4.8 Illustrative Examples -- 4.9 Concluding Remarks -- 4.10 Problems -- References -- Chapter 5 Particle Filtering -- 5.1 Introduction -- 5.2 Motivation for Use of Particle Filtering -- 5.3 The Basic Idea -- 5.4 The Choice of Proposal Distribution and Resampling -- 5.5 Some Particle Filtering Methods -- 5.6 Handling Constant Parameters -- 5.7 Rao-Blackwellization -- 5.8 Prediction -- 5.9 Smoothing -- 5.10 Convergence Issues -- 5.11 Computational Issues and Hardware Implementation -- 5.12 Acknowledgments.
5.13 Exercises -- References -- Chapter 6 Nonlinear Sequential State Estimation for Solving Pattern-Classification Problems -- 6.1 Introduction -- 6.2 Back-Propagation and Support Vector Machine-Learning Algorithms: Review -- 6.3 Supervised Training Framework of MLPs Using Nonlinear Sequential State Estimation -- 6.4 The Extended Kalman Filter -- 6.5 Experimental Comparison of the Extended Kalman Filtering Algorithm with the Back-Propagation and Support Vector Machine Learning Algorithms -- 6.6 Concluding Remarks -- 6.7 Problems -- References -- Chapter 7 Bandwidth Extension of Telephony Speech -- 7.1 Introduction -- 7.2 Organization of the Chapter -- 7.3 Nonmodel-Based Algorithms for Bandwidth Extension -- 7.4 Basics -- 7.5 Model-Based Algorithms for Bandwidth Extension -- 7.6 Evaluation of Bandwidth Extension Algorithms -- 7.7 Conclusion -- 7.8 Problems -- References -- Index. |
| Record Nr. | UNINA-9910140741803321 |
| Hoboken, N.J., : Wiley-IEEE, c2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Applications of high temperature superconductors to electric power equipment / / Swarn Singh Kalsi
| Applications of high temperature superconductors to electric power equipment / / Swarn Singh Kalsi |
| Autore | Kalsi Swarn Singh |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley-IEEE, , c2010 |
| Descrizione fisica | 1 online resource (334 p.) |
| Disciplina |
621.31/042
621.31042 |
| Soggetto topico |
Electric machinery - Materials
Electric power systems - Equipment and supplies High temperature superconductors - Industrial applications |
| ISBN |
1-118-11009-9
1-283-02505-1 9786613025050 0-470-87789-8 0-470-87788-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Introduction -- HTS Superconductors -- Cooling and Thermal Insulation Systems -- Rotating AC Machines -- Rotating DC Homopolar Machines -- Synchronous AC Homopolar Machines -- Transformers -- Fault Current Limiters -- Power Cables -- Maglev Transport -- Magnet Applications -- About the Author -- Index. |
| Record Nr. | UNINA-9910139211903321 |
|
Kalsi Swarn Singh
|
||
| Hoboken, New Jersey : , : Wiley-IEEE, , c2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Applications of high temperature superconductors to electric power equipment / / Swarn Singh Kalsi
| Applications of high temperature superconductors to electric power equipment / / Swarn Singh Kalsi |
| Autore | Kalsi Swarn Singh |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley-IEEE, , c2010 |
| Descrizione fisica | 1 online resource (334 p.) |
| Disciplina |
621.31/042
621.31042 |
| Soggetto topico |
Electric machinery - Materials
Electric power systems - Equipment and supplies High temperature superconductors - Industrial applications |
| ISBN |
1-118-11009-9
1-283-02505-1 9786613025050 0-470-87789-8 0-470-87788-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Introduction -- HTS Superconductors -- Cooling and Thermal Insulation Systems -- Rotating AC Machines -- Rotating DC Homopolar Machines -- Synchronous AC Homopolar Machines -- Transformers -- Fault Current Limiters -- Power Cables -- Maglev Transport -- Magnet Applications -- About the Author -- Index. |
| Record Nr. | UNINA-9910831080303321 |
|
Kalsi Swarn Singh
|
||
| Hoboken, New Jersey : , : Wiley-IEEE, , c2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Applications of high temperature superconductors to electric power equipment / / Swarn Singh Kalsi
| Applications of high temperature superconductors to electric power equipment / / Swarn Singh Kalsi |
| Autore | Kalsi Swarn Singh |
| Pubbl/distr/stampa | Hoboken, NJ, : Wiley-IEEE, c2010 |
| Descrizione fisica | 1 online resource (334 p.) |
| Disciplina |
621.31/042
621.31042 |
| Soggetto topico |
Electric machinery - Materials
Electric power systems - Equipment and supplies High temperature superconductors - Industrial applications |
| ISBN |
1-118-11009-9
1-283-02505-1 9786613025050 0-470-87789-8 0-470-87788-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Introduction -- HTS Superconductors -- Cooling and Thermal Insulation Systems -- Rotating AC Machines -- Rotating DC Homopolar Machines -- Synchronous AC Homopolar Machines -- Transformers -- Fault Current Limiters -- Power Cables -- Maglev Transport -- Magnet Applications -- About the Author -- Index. |
| Record Nr. | UNINA-9910877748103321 |
|
Kalsi Swarn Singh
|
||
| Hoboken, NJ, : Wiley-IEEE, c2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Blockchain for distributed systems security / / edited by Sachin S. Shetty, Charles A. Kamhoua, Laurent L. Njilla
| Blockchain for distributed systems security / / edited by Sachin S. Shetty, Charles A. Kamhoua, Laurent L. Njilla |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley-IEEE, , [2019] |
| Descrizione fisica | 1 online resource (347 pages) : illustrations |
| Disciplina | 005.824 |
| Soggetto topico |
Blockchains (Databases)
Internet auctions - Security measures |
| ISBN |
1-119-51958-6
1-119-51962-4 1-119-51959-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Foreword xiii -- Preface xv -- List of Contributors xix -- Part I Introduction to Blockchain 1 -- 1 Introduction 3 /Sachin S. Shetty, Laurent Njilla, and Charles A. Kamhoua -- 1.1 Blockchain Overview 3 -- 1.1.1 Blockchain Building Blocks 5 -- 1.1.2 Blockchain Commercial Use Cases 6 -- 1.1.3 Blockchain Military Cyber Operations Use Cases 11 -- 1.1.4 Blockchain Challenges 13 -- 1.2 Overview of the Book 16 -- 1.2.1 Chapter 2: Distributed Consensus Protocols and Algorithms 16 -- 1.2.2 Chapter 3: Overview of Attack Surfaces in Blockchain 17 -- 1.2.3 Chapter 4: Data Provenance in Cloud Storage with Blockchain 17 -- 1.2.4 Chapter 5: Blockchain-based Solution to Automotive Security and Privacy 18 -- 1.2.5 Chapter 6: Blockchain-based Dynamic Key Management for IoT-Transportation Security Protection 19 -- 1.2.6 Chapter 7: Blockchain-enabled Information Sharing Framework for Cybersecurity 19 -- 1.2.7 Chapter 8: Blockcloud Security Analysis 20 -- 1.2.8 Chapter 9: Security and Privacy of Permissioned and Permissionless Blockchain 20 -- 1.2.9 Chapter 10: Shocking Public Blockchains’ Memory with Unconfirmed Transactions-New DDoS Attacks and Countermeasures 21 -- 1.2.10 Chapter 11: Preventing Digital Currency Miners From Launching Attacks Against Mining Pools by a Reputation-Based Paradigm 21 -- 1.2.11 Chapter 12: Private Blockchain Configurations for Improved IoT Security 22 -- 1.2.12 Chapter 13: Blockchain Evaluation Platform 22 -- References 23 -- 2 Distributed Consensus Protocols and Algorithms 25 /Yang Xiao, Ning Zhang, Jin Li, Wenjing Lou, and Y. Thomas Hou -- 2.1 Introduction 25 -- 2.2 Fault-tolerant Consensus in a Distributed System 26 -- 2.2.1 The System Model 26 -- 2.2.2 BFT Consensus 28 -- 2.2.3 The OM Algorithm 29 -- 2.2.4 Practical Consensus Protocols in Distributed Computing 30 -- 2.3 The Nakamoto Consensus 37 -- 2.3.1 The Consensus Problem 38 -- 2.3.2 Network Model 38 -- 2.3.3 The Consensus Protocol 39 -- 2.4 Emerging Blockchain Consensus Algorithms 40 -- 2.4.1 Proof of Stake 41.
2.4.2 BFT-based Consensus 42 -- 2.4.3 Proof of Elapsed Time (PoET) 44 -- 2.4.4 Ripple 45 -- 2.5 Evaluation and Comparison 47 -- 2.6 Summary 47 -- Acknowledgment 49 -- References 49 -- 3 Overview of Attack Surfaces in Blockchain 51 /Muhammad Saad, Jeffrey Spaulding, Laurent Njilla, Charles A. Kamhoua, DaeHun Nyang, and Aziz Mohaisen -- 3.1 Introduction 51 -- 3.2 Overview of Blockchain and its Operations 53 -- 3.3 Blockchain Attacks 54 -- 3.3.1 Blockchain Fork 54 -- 3.3.2 Stale Blocks and Orphaned Blocks 54 -- 3.3.3 Countering Blockchain Structure Attacks 55 -- 3.4 Blockchain’s Peer-to-Peer System 55 -- 3.4.1 Selfish Mining 56 -- 3.4.2 The 51% Attack 57 -- 3.4.3 DNS Attacks 57 -- 3.4.4 DDoS Attacks 58 -- 3.4.5 Consensus Delay 59 -- 3.4.6 Countering Peer-to-Peer Attacks 59 -- 3.5 Application Oriented Attacks 60 -- 3.5.1 Blockchain Ingestion 60 -- 3.5.2 Double Spending 60 -- 3.5.3 Wallet Theft 61 -- 3.5.4 Countering Application Oriented Attacks 61 -- 3.6 Related Work 61 -- 3.7 Conclusion and Future Work 62 -- References 62 -- Part II Blockchain Solutions for Distributed System Security 67 -- 4 ProvChain: Blockchain-based Cloud Data Provenance 69 /Xueping Liang, Sachin S. Shetty, Deepak Tosh, Laurent Njilla, Charles A. Kamhoua, and Kevin Kwiat -- 4.1 Introduction 69 -- 4.2 Background and Related Work 70 -- 4.2.1 Data Provenance 70 -- 4.2.2 Data Provenance in the Cloud 71 -- 4.2.3 Blockchain 73 -- 4.2.4 Blockchain and Data Provenance 74 -- 4.3 ProvChain Architecture 75 -- 4.3.1 Architecture Overview 76 -- 4.3.2 Preliminaries and Concepts 77 -- 4.3.3 Threat Model 78 -- 4.3.4 Key Establishment 78 -- 4.4 ProvChain Implementation 79 -- 4.4.1 Provenance Data Collection and Storage 80 -- 4.4.2 Provenance Data Validation 83 -- 4.5 Evaluation 85 -- 4.5.1 Summary of ProvChain’s Capabilities 85 -- 4.5.2 Performance and Overhead 86 -- 4.6 Conclusions and Future Work 90 -- Acknowledgment 91 -- References 92 -- 5 A Blockchain-based Solution to Automotive Security and Privacy 95 /Ali Dorri, Marco Steger, Salil S. Kanhere, and Raja Jurdak. 5.1 Introduction 95 -- 5.2 An Introduction to Blockchain 98 -- 5.3 The Proposed Framework 101 -- 5.4 Applications 103 -- 5.4.1 Remote Software Updates 103 -- 5.4.2 Insurance 105 -- 5.4.3 Electric Vehicles and Smart Charging Services 105 -- 5.4.4 Car-sharing Services 106 -- 5.4.5 Supply Chain 106 -- 5.4.6 Liability 107 -- 5.5 Evaluation and Discussion 108 -- 5.5.1 Security and Privacy Analysis 108 -- 5.5.2 Performance Evaluation 109 -- 5.6 Related Works 112 -- 5.7 Conclusion 113 -- References 114 -- 6 Blockchain-based Dynamic Key Management for IoT-Transportation Security Protection 117 /Ao Lei, Yue Cao, Shihan Bao, Philip Asuquom, Haitham Cruickshank, and Zhili Sun -- 6.1 Introduction 117 -- 6.2 Use Case 119 -- 6.2.1 Message Handover in VCS 120 -- 6.3 Blockchain-based Dynamic Key Management Scheme 124 -- 6.4 Dynamic Transaction Collection Algorithm 125 -- 6.4.1 Transaction Format 125 -- 6.4.2 Block Format 127 -- 6.5 Time Composition 128 -- 6.5.1 Dynamic Transaction Collection Algorithm 129 -- 6.6 Performance Evaluation 130 -- 6.6.1 Experimental Assumptions and Setup 130 -- 6.6.2 Processing Time of Cryptographic Schemes 132 -- 6.6.3 Handover Time 133 -- 6.6.4 Performance of the Dynamic Transaction Collection Algorithm 135 -- 6.7 Conclusion and Future Work 138 -- References 140 -- 7 Blockchain-enabled Information Sharing Framework for Cybersecurity 143 /Abdulhamid Adebayo, Danda B. Rawat, Laurent Njilla, and Charles A. Kamhoua -- 7.1 Introduction 143 -- 7.2 The BIS Framework 145 -- 7.3 Transactions on BIS 146 -- 7.4 Cyberattack Detection and Information Sharing 147 -- 7.5 Cross-group Attack Game in Blockchain-based BIS Framework: One-way Attack 149 -- 7.6 Cross-group Attack Game in Blockchain-based BIS Framework: Two-way Attack 151 -- 7.7 Stackelberg Game for Cyberattack and Defense Analysis 152 -- 7.8 Conclusion 156 -- References 157 -- Part III Blockchain Security 159 -- 8 Blockcloud Security Analysis 161 /Deepak Tosh, Sachin S. Shetty, Xueping Liang, Laurent Njilla, Charles A. Kamhoua, and Kevin Kwiat. 8.1 Introduction 161 -- 8.2 Blockchain Consensus Mechanisms 163 -- 8.2.1 Proof-of-Work (PoW) Consensus 164 -- 8.2.2 Proof-of-Stake (PoS) Consensus 165 -- 8.2.3 Proof-of-Activity (PoA) Consensus 167 -- 8.2.4 Practical Byzantine Fault Tolerance (PBFT) Consensus 168 -- 8.2.5 Proof-of-Elapsed-Time (PoET) Consensus 169 -- 8.2.6 Proof-of-Luck (PoL) Consensus 170 -- 8.2.7 Proof-of-Space (PoSpace) Consensus 170 -- 8.3 Blockchain Cloud and Associated Vulnerabilities 171 -- 8.3.1 Blockchain and Cloud Security 171 -- 8.3.2 Blockchain Cloud Vulnerabilities 174 -- 8.4 System Model 179 -- 8.5 Augmenting with Extra Hash Power 180 -- 8.6 Disruptive Attack Strategy Analysis 181 -- 8.6.1 Proportional Reward 181 -- 8.6.2 Pay-per-last N-shares (PPLNS) Reward 184 -- 8.7 Simulation Results and Discussion 187 -- 8.8 Conclusions and Future Directions 188 -- Acknowledgment 190 -- References 190 -- 9 Permissioned and Permissionless Blockchains 193 /Andrew Miller -- 9.1 Introduction 193 -- 9.2 On Choosing Your Peers Wisely 194 -- 9.3 Committee Election Mechanisms 196 -- 9.4 Privacy in Permissioned and Permissionless Blockchains 199 -- 9.5 Conclusion 201 -- References 202 -- 10 Shocking Blockchain’s Memory with Unconfirmed Transactions: New DDoS Attacks and Countermeasures 205 /Muhammad Saad, Laurent Njilla, Charles A. Kamhoua, Kevin Kwiat, and Aziz Mohaisen -- 10.1 Introduction 205 -- 10.2 Related Work 207 -- 10.3 An Overview of Blockchain and Lifecycle 208 -- 10.3.1 DDoS Attack on Mempools 210 -- 10.3.2 Data Collection for Evaluation 210 -- 10.4 Threat Model 211 -- 10.5 Attack Procedure 212 -- 10.5.1 The Distribution Phase 214 -- 10.5.2 The Attack Phase 214 -- 10.5.3 Attack Cost 214 -- 10.6 Countering the Mempool Attack 215 -- 10.6.1 Fee-based Mempool Design 216 -- 10.6.2 Age-based Countermeasures 221 -- 10.7 Experiment and Results 224 -- 10.8 Conclusion 227 -- References 227 -- 11 Preventing Digital Currency Miners from Launching Attacks Against Mining Pools Using a Reputation-based Paradigm 233 /Mehrdad Nojoumian, Arash Golchubian, Laurent Njilla, Kevin Kwiat, and Charles A. Kamhoua. 11.1 Introduction 233 -- 11.2 Preliminaries 234 -- 11.2.1 Digital Currencies: Terminologies and Mechanics 234 -- 11.2.2 Game Theory: Basic Notions and Definitions 235 -- 11.3 Literature Review 236 -- 11.4 Reputation-based Mining Model and Setting 238 -- 11.5 Mining in a Reputation-based Model 240 -- 11.5.1 Prevention of the Re-entry Attack 240 -- 11.5.2 Technical Discussion on Detection Mechanisms 241 -- 11.5.3 Colluding Miner’s Dilemma 243 -- 11.5.4 Repeated Mining Game 244 -- 11.5.5 Colluding Miners’ Preferences 245 -- 11.5.6 Colluding Miners’ Utilities 245 -- 11.6 Evaluation of Our Model Using Game-theoretical Analyses 246 -- 11.7 Concluding Remarks 248 -- Acknowledgment 249 -- References 249 -- Part IV Blockchain Implementation 253 -- 12 Private Blockchain Configurations for Improved IoT Security 255 /Adriaan Larmuseau and Devu Manikantan Shila -- 12.1 Introduction 255 -- 12.2 Blockchain-enabled Gateway 257 -- 12.2.1 Advantages 257 -- 12.2.2 Limitations 258 -- 12.2.3 Private Ethereum Gateways for Access Control 259 -- 12.2.4 Evaluation 262 -- 12.3 Blockchain-enabled Smart End Devices 263 -- 12.3.1 Advantages 263 -- 12.3.2 Limitations 264 -- 12.3.3 Private Hyperledger Blockchain-enabled Smart Sensor Devices 264 -- 12.3.4 Evaluation 269 -- 12.4 Related Work 270 -- 12.5 Conclusion 271 -- References 271 -- 13 Blockchain Evaluation Platform 275 /Peter Foytik and Sachin S. Shetty -- 13.1 Introduction 275 -- 13.1.1 Architecture 276 -- 13.1.2 Distributed Ledger 276 -- 13.1.3 Participating Nodes 277 -- 13.1.4 Communication 277 -- 13.1.5 Consensus 278 -- 13.2 Hyperledger Fabric 279 -- 13.2.1 Node Types 279 -- 13.2.2 Docker 280 -- 13.2.3 Hyperledger Fabric Example Exercise 281 -- 13.2.4 Running the First Network 281 -- 13.2.5 Running the Kafka Network 286 -- 13.3 Measures of Performance 291 -- 13.3.1 Performance Metrics With the Proof-of-Stake Simulation 293 -- 13.3.2 Performance Measures With the Hyperledger Fabric Example 296 -- 13.4 Simple Blockchain Simulation 300. 13.5 Blockchain Simulation Introduction 303 -- 13.5.1 Methodology 304 -- 13.5.2 Simulation Integration With Live Blockchain 304 -- 13.5.3 Simulation Integration With Simulated Blockchain 306 -- 13.5.4 Verification and Validation 306 -- 13.5.5 Example 307 -- 13.6 Conclusion and Future Work 309 -- References 310 -- 14 Summary and Future Work 311 /Sachin S. Shetty, Laurent Njilla, and Charles A. Kamhoua -- 14.1 Introduction 311 -- 14.2 Blockchain and Cloud Security 312 -- 14.3 Blockchain and IoT Security 312 -- 14.4 Blockchain Security and Privacy 314 -- 14.5 Experimental Testbed and Performance Evaluation 316 -- 14.6 The Future 316 -- Index 319. |
| Record Nr. | UNINA-9910555114003321 |
| Hoboken, New Jersey : , : Wiley-IEEE, , [2019] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Blockchain for distributed systems security / / edited by Sachin S. Shetty, Charles A. Kamhoua, Laurent L. Njilla
| Blockchain for distributed systems security / / edited by Sachin S. Shetty, Charles A. Kamhoua, Laurent L. Njilla |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley-IEEE, , [2019] |
| Descrizione fisica | 1 online resource (347 pages) : illustrations |
| Disciplina | 005.824 |
| Soggetto topico |
Blockchains (Databases)
Internet auctions - Security measures |
| ISBN |
1-119-51958-6
1-119-51962-4 1-119-51959-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Foreword xiii -- Preface xv -- List of Contributors xix -- Part I Introduction to Blockchain 1 -- 1 Introduction 3 /Sachin S. Shetty, Laurent Njilla, and Charles A. Kamhoua -- 1.1 Blockchain Overview 3 -- 1.1.1 Blockchain Building Blocks 5 -- 1.1.2 Blockchain Commercial Use Cases 6 -- 1.1.3 Blockchain Military Cyber Operations Use Cases 11 -- 1.1.4 Blockchain Challenges 13 -- 1.2 Overview of the Book 16 -- 1.2.1 Chapter 2: Distributed Consensus Protocols and Algorithms 16 -- 1.2.2 Chapter 3: Overview of Attack Surfaces in Blockchain 17 -- 1.2.3 Chapter 4: Data Provenance in Cloud Storage with Blockchain 17 -- 1.2.4 Chapter 5: Blockchain-based Solution to Automotive Security and Privacy 18 -- 1.2.5 Chapter 6: Blockchain-based Dynamic Key Management for IoT-Transportation Security Protection 19 -- 1.2.6 Chapter 7: Blockchain-enabled Information Sharing Framework for Cybersecurity 19 -- 1.2.7 Chapter 8: Blockcloud Security Analysis 20 -- 1.2.8 Chapter 9: Security and Privacy of Permissioned and Permissionless Blockchain 20 -- 1.2.9 Chapter 10: Shocking Public Blockchains’ Memory with Unconfirmed Transactions-New DDoS Attacks and Countermeasures 21 -- 1.2.10 Chapter 11: Preventing Digital Currency Miners From Launching Attacks Against Mining Pools by a Reputation-Based Paradigm 21 -- 1.2.11 Chapter 12: Private Blockchain Configurations for Improved IoT Security 22 -- 1.2.12 Chapter 13: Blockchain Evaluation Platform 22 -- References 23 -- 2 Distributed Consensus Protocols and Algorithms 25 /Yang Xiao, Ning Zhang, Jin Li, Wenjing Lou, and Y. Thomas Hou -- 2.1 Introduction 25 -- 2.2 Fault-tolerant Consensus in a Distributed System 26 -- 2.2.1 The System Model 26 -- 2.2.2 BFT Consensus 28 -- 2.2.3 The OM Algorithm 29 -- 2.2.4 Practical Consensus Protocols in Distributed Computing 30 -- 2.3 The Nakamoto Consensus 37 -- 2.3.1 The Consensus Problem 38 -- 2.3.2 Network Model 38 -- 2.3.3 The Consensus Protocol 39 -- 2.4 Emerging Blockchain Consensus Algorithms 40 -- 2.4.1 Proof of Stake 41.
2.4.2 BFT-based Consensus 42 -- 2.4.3 Proof of Elapsed Time (PoET) 44 -- 2.4.4 Ripple 45 -- 2.5 Evaluation and Comparison 47 -- 2.6 Summary 47 -- Acknowledgment 49 -- References 49 -- 3 Overview of Attack Surfaces in Blockchain 51 /Muhammad Saad, Jeffrey Spaulding, Laurent Njilla, Charles A. Kamhoua, DaeHun Nyang, and Aziz Mohaisen -- 3.1 Introduction 51 -- 3.2 Overview of Blockchain and its Operations 53 -- 3.3 Blockchain Attacks 54 -- 3.3.1 Blockchain Fork 54 -- 3.3.2 Stale Blocks and Orphaned Blocks 54 -- 3.3.3 Countering Blockchain Structure Attacks 55 -- 3.4 Blockchain’s Peer-to-Peer System 55 -- 3.4.1 Selfish Mining 56 -- 3.4.2 The 51% Attack 57 -- 3.4.3 DNS Attacks 57 -- 3.4.4 DDoS Attacks 58 -- 3.4.5 Consensus Delay 59 -- 3.4.6 Countering Peer-to-Peer Attacks 59 -- 3.5 Application Oriented Attacks 60 -- 3.5.1 Blockchain Ingestion 60 -- 3.5.2 Double Spending 60 -- 3.5.3 Wallet Theft 61 -- 3.5.4 Countering Application Oriented Attacks 61 -- 3.6 Related Work 61 -- 3.7 Conclusion and Future Work 62 -- References 62 -- Part II Blockchain Solutions for Distributed System Security 67 -- 4 ProvChain: Blockchain-based Cloud Data Provenance 69 /Xueping Liang, Sachin S. Shetty, Deepak Tosh, Laurent Njilla, Charles A. Kamhoua, and Kevin Kwiat -- 4.1 Introduction 69 -- 4.2 Background and Related Work 70 -- 4.2.1 Data Provenance 70 -- 4.2.2 Data Provenance in the Cloud 71 -- 4.2.3 Blockchain 73 -- 4.2.4 Blockchain and Data Provenance 74 -- 4.3 ProvChain Architecture 75 -- 4.3.1 Architecture Overview 76 -- 4.3.2 Preliminaries and Concepts 77 -- 4.3.3 Threat Model 78 -- 4.3.4 Key Establishment 78 -- 4.4 ProvChain Implementation 79 -- 4.4.1 Provenance Data Collection and Storage 80 -- 4.4.2 Provenance Data Validation 83 -- 4.5 Evaluation 85 -- 4.5.1 Summary of ProvChain’s Capabilities 85 -- 4.5.2 Performance and Overhead 86 -- 4.6 Conclusions and Future Work 90 -- Acknowledgment 91 -- References 92 -- 5 A Blockchain-based Solution to Automotive Security and Privacy 95 /Ali Dorri, Marco Steger, Salil S. Kanhere, and Raja Jurdak. 5.1 Introduction 95 -- 5.2 An Introduction to Blockchain 98 -- 5.3 The Proposed Framework 101 -- 5.4 Applications 103 -- 5.4.1 Remote Software Updates 103 -- 5.4.2 Insurance 105 -- 5.4.3 Electric Vehicles and Smart Charging Services 105 -- 5.4.4 Car-sharing Services 106 -- 5.4.5 Supply Chain 106 -- 5.4.6 Liability 107 -- 5.5 Evaluation and Discussion 108 -- 5.5.1 Security and Privacy Analysis 108 -- 5.5.2 Performance Evaluation 109 -- 5.6 Related Works 112 -- 5.7 Conclusion 113 -- References 114 -- 6 Blockchain-based Dynamic Key Management for IoT-Transportation Security Protection 117 /Ao Lei, Yue Cao, Shihan Bao, Philip Asuquom, Haitham Cruickshank, and Zhili Sun -- 6.1 Introduction 117 -- 6.2 Use Case 119 -- 6.2.1 Message Handover in VCS 120 -- 6.3 Blockchain-based Dynamic Key Management Scheme 124 -- 6.4 Dynamic Transaction Collection Algorithm 125 -- 6.4.1 Transaction Format 125 -- 6.4.2 Block Format 127 -- 6.5 Time Composition 128 -- 6.5.1 Dynamic Transaction Collection Algorithm 129 -- 6.6 Performance Evaluation 130 -- 6.6.1 Experimental Assumptions and Setup 130 -- 6.6.2 Processing Time of Cryptographic Schemes 132 -- 6.6.3 Handover Time 133 -- 6.6.4 Performance of the Dynamic Transaction Collection Algorithm 135 -- 6.7 Conclusion and Future Work 138 -- References 140 -- 7 Blockchain-enabled Information Sharing Framework for Cybersecurity 143 /Abdulhamid Adebayo, Danda B. Rawat, Laurent Njilla, and Charles A. Kamhoua -- 7.1 Introduction 143 -- 7.2 The BIS Framework 145 -- 7.3 Transactions on BIS 146 -- 7.4 Cyberattack Detection and Information Sharing 147 -- 7.5 Cross-group Attack Game in Blockchain-based BIS Framework: One-way Attack 149 -- 7.6 Cross-group Attack Game in Blockchain-based BIS Framework: Two-way Attack 151 -- 7.7 Stackelberg Game for Cyberattack and Defense Analysis 152 -- 7.8 Conclusion 156 -- References 157 -- Part III Blockchain Security 159 -- 8 Blockcloud Security Analysis 161 /Deepak Tosh, Sachin S. Shetty, Xueping Liang, Laurent Njilla, Charles A. Kamhoua, and Kevin Kwiat. 8.1 Introduction 161 -- 8.2 Blockchain Consensus Mechanisms 163 -- 8.2.1 Proof-of-Work (PoW) Consensus 164 -- 8.2.2 Proof-of-Stake (PoS) Consensus 165 -- 8.2.3 Proof-of-Activity (PoA) Consensus 167 -- 8.2.4 Practical Byzantine Fault Tolerance (PBFT) Consensus 168 -- 8.2.5 Proof-of-Elapsed-Time (PoET) Consensus 169 -- 8.2.6 Proof-of-Luck (PoL) Consensus 170 -- 8.2.7 Proof-of-Space (PoSpace) Consensus 170 -- 8.3 Blockchain Cloud and Associated Vulnerabilities 171 -- 8.3.1 Blockchain and Cloud Security 171 -- 8.3.2 Blockchain Cloud Vulnerabilities 174 -- 8.4 System Model 179 -- 8.5 Augmenting with Extra Hash Power 180 -- 8.6 Disruptive Attack Strategy Analysis 181 -- 8.6.1 Proportional Reward 181 -- 8.6.2 Pay-per-last N-shares (PPLNS) Reward 184 -- 8.7 Simulation Results and Discussion 187 -- 8.8 Conclusions and Future Directions 188 -- Acknowledgment 190 -- References 190 -- 9 Permissioned and Permissionless Blockchains 193 /Andrew Miller -- 9.1 Introduction 193 -- 9.2 On Choosing Your Peers Wisely 194 -- 9.3 Committee Election Mechanisms 196 -- 9.4 Privacy in Permissioned and Permissionless Blockchains 199 -- 9.5 Conclusion 201 -- References 202 -- 10 Shocking Blockchain’s Memory with Unconfirmed Transactions: New DDoS Attacks and Countermeasures 205 /Muhammad Saad, Laurent Njilla, Charles A. Kamhoua, Kevin Kwiat, and Aziz Mohaisen -- 10.1 Introduction 205 -- 10.2 Related Work 207 -- 10.3 An Overview of Blockchain and Lifecycle 208 -- 10.3.1 DDoS Attack on Mempools 210 -- 10.3.2 Data Collection for Evaluation 210 -- 10.4 Threat Model 211 -- 10.5 Attack Procedure 212 -- 10.5.1 The Distribution Phase 214 -- 10.5.2 The Attack Phase 214 -- 10.5.3 Attack Cost 214 -- 10.6 Countering the Mempool Attack 215 -- 10.6.1 Fee-based Mempool Design 216 -- 10.6.2 Age-based Countermeasures 221 -- 10.7 Experiment and Results 224 -- 10.8 Conclusion 227 -- References 227 -- 11 Preventing Digital Currency Miners from Launching Attacks Against Mining Pools Using a Reputation-based Paradigm 233 /Mehrdad Nojoumian, Arash Golchubian, Laurent Njilla, Kevin Kwiat, and Charles A. Kamhoua. 11.1 Introduction 233 -- 11.2 Preliminaries 234 -- 11.2.1 Digital Currencies: Terminologies and Mechanics 234 -- 11.2.2 Game Theory: Basic Notions and Definitions 235 -- 11.3 Literature Review 236 -- 11.4 Reputation-based Mining Model and Setting 238 -- 11.5 Mining in a Reputation-based Model 240 -- 11.5.1 Prevention of the Re-entry Attack 240 -- 11.5.2 Technical Discussion on Detection Mechanisms 241 -- 11.5.3 Colluding Miner’s Dilemma 243 -- 11.5.4 Repeated Mining Game 244 -- 11.5.5 Colluding Miners’ Preferences 245 -- 11.5.6 Colluding Miners’ Utilities 245 -- 11.6 Evaluation of Our Model Using Game-theoretical Analyses 246 -- 11.7 Concluding Remarks 248 -- Acknowledgment 249 -- References 249 -- Part IV Blockchain Implementation 253 -- 12 Private Blockchain Configurations for Improved IoT Security 255 /Adriaan Larmuseau and Devu Manikantan Shila -- 12.1 Introduction 255 -- 12.2 Blockchain-enabled Gateway 257 -- 12.2.1 Advantages 257 -- 12.2.2 Limitations 258 -- 12.2.3 Private Ethereum Gateways for Access Control 259 -- 12.2.4 Evaluation 262 -- 12.3 Blockchain-enabled Smart End Devices 263 -- 12.3.1 Advantages 263 -- 12.3.2 Limitations 264 -- 12.3.3 Private Hyperledger Blockchain-enabled Smart Sensor Devices 264 -- 12.3.4 Evaluation 269 -- 12.4 Related Work 270 -- 12.5 Conclusion 271 -- References 271 -- 13 Blockchain Evaluation Platform 275 /Peter Foytik and Sachin S. Shetty -- 13.1 Introduction 275 -- 13.1.1 Architecture 276 -- 13.1.2 Distributed Ledger 276 -- 13.1.3 Participating Nodes 277 -- 13.1.4 Communication 277 -- 13.1.5 Consensus 278 -- 13.2 Hyperledger Fabric 279 -- 13.2.1 Node Types 279 -- 13.2.2 Docker 280 -- 13.2.3 Hyperledger Fabric Example Exercise 281 -- 13.2.4 Running the First Network 281 -- 13.2.5 Running the Kafka Network 286 -- 13.3 Measures of Performance 291 -- 13.3.1 Performance Metrics With the Proof-of-Stake Simulation 293 -- 13.3.2 Performance Measures With the Hyperledger Fabric Example 296 -- 13.4 Simple Blockchain Simulation 300. 13.5 Blockchain Simulation Introduction 303 -- 13.5.1 Methodology 304 -- 13.5.2 Simulation Integration With Live Blockchain 304 -- 13.5.3 Simulation Integration With Simulated Blockchain 306 -- 13.5.4 Verification and Validation 306 -- 13.5.5 Example 307 -- 13.6 Conclusion and Future Work 309 -- References 310 -- 14 Summary and Future Work 311 /Sachin S. Shetty, Laurent Njilla, and Charles A. Kamhoua -- 14.1 Introduction 311 -- 14.2 Blockchain and Cloud Security 312 -- 14.3 Blockchain and IoT Security 312 -- 14.4 Blockchain Security and Privacy 314 -- 14.5 Experimental Testbed and Performance Evaluation 316 -- 14.6 The Future 316 -- Index 319. |
| Record Nr. | UNINA-9910676564003321 |
| Hoboken, New Jersey : , : Wiley-IEEE, , [2019] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computational intelligence in bioinformatics / / edited by Gary B. Fogel, David W. Corne, Yi Pan
| Computational intelligence in bioinformatics / / edited by Gary B. Fogel, David W. Corne, Yi Pan |
| Pubbl/distr/stampa | New York, : Wiley-IEEE, c2008 |
| Descrizione fisica | 1 online resource (377 p.) |
| Disciplina |
572.028563
572.80285 |
| Altri autori (Persone) |
CorneDavid
FogelGary <1968-> PanYi <1960-> |
| Collana | IEEE Press series on computational intelligence |
| Soggetto topico |
Bioinformatics
Computational intelligence |
| ISBN |
0-470-65215-2
1-281-22169-4 9786611221690 0-470-19909-1 0-470-19908-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Preface -- Contributors -- Part One Gene Expression Analysis and Systems Biology -- 1. Hybrid of Neural Classifi er and Swarm Intelligence in Multiclass Cancer Diagnosis with Gene Expression Signatures (Rui Xu, Georgios C. Anagnostopoulos, and Donald C. Wunsch II) -- 1.1 Introduction -- 1.2 Methods and Systems -- 1.3 Experimental Results -- 1.4 Conclusions -- 2. Classifying Gene Expression Profi les with Evolutionary Computation (Jin-Hyuk Hong and Sung-Bae Cho) -- 2.1 DNA Microarray Data Classifi cation -- 2.2 Evolutionary Approach to the Problem -- 2.3 Gene Selection with Speciated Genetic Algorithm -- 2.4 Cancer Classifi ction Based on Ensemble Genetic Programming -- 2.5 Conclusion -- 3. Finding Clusters in Gene Expression Data Using EvoCluster (Patrick C. H. Ma, Keith C. C. Chan, and Xin Yao) -- 3.1 Introduction -- 3.2 Related Work -- 3.3 Evolutionary Clustering Algorithm -- 3.4 Experimental Results -- 3.5 Conclusions -- 4. Gene Networks and Evolutionary Computation (Jennifer Hallinan) -- 4.1 Introduction -- 4.2 Evolutionary Optimization -- 4.3 Computational Network Modeling -- 4.4 Extending Reach of Gene Networks -- 4.5 Network Topology Analysis -- 4.6 Summary -- Part Two Sequence Analysis and Feature Detection -- 5. Fuzzy-Granular Methods for Identifying Marker Genes from Microarray Expression Data (Yuanchen He, Yuchun Tang, Yan-Qing Zhang, and Rajshekhar Sunderraman) -- 5.1 Introduction -- 5.2 Traditional Algorithms for Gene Selection -- 5.3 New Fuzzy-Granular-Based Algorithm for Gene Selection -- 5.4 Simulation -- 5.5 Conclusions -- 6. Evolutionary Feature Selection for Bioinformatics (Laetitia Jourdan, Clarisse Dhaenens, and El-Ghazali Talbi) -- 6.1 Introduction -- 6.2 Evolutionary Algorithms for Feature Selection -- 6.3 Feature Selection for Clustering in Bioinformatics -- 6.4 Feature Selection for Classifi cation in Bioinformatics -- 6.5 Frameworks and Data Sets -- 6.6 Conclusion -- 7. Fuzzy Approaches for the Analysis CpG Island Methylation Patterns (Ozy Sjahputera, Mihail Popescu, James M. Keller, and Charles W. Caldwell).
7.1 Introduction -- 7.2 Methods -- 7.3 Biological Signifi cance -- 7.4 Conclusions -- Part Three Molecular Structure and Phylogenetics -- 8. Protein-Ligand Docking with Evolutionary Algorithms(Rene Thomsen) -- 8.1 Introduction -- 8.2 Biochemical Background -- 8.3 The Docking Problem -- 8.4 Protein-Ligand Docking Algorithms -- 8.5 Evolutionary Algorithms -- 8.6 Effect of Variation Operators -- 8.7 Differential Evolution -- 8.8 Evaluating Docking Methods -- 8.9 Comparison between Docking Methods -- 8.10 Summary -- 8.11 Future Research Topics -- 9. RNA Secondary Structure Prediction Employing Evolutionary Algorithms (Kay C. Wiese, Alain A. Deschanes, and Andrew G. Hendriks) -- 9.1 Introduction -- 9.2 Thermodynamic Models -- 9.3 Methods -- 9.4 Results -- 9.5 Conclusion -- 10. Machine Learning Approach for Prediction of Human Mitochondrial Proteins (Zhong Huang, Xuheng Xu, and Xiaohua Hu) -- 10.1 Introduction -- 10.2 Methods and Systems -- 10.3 Results and Discussion -- 10.4 Conclusions -- 11. Phylogenetic Inference Using Evolutionary Algorithms(Clare Bates Congdon) -- 11.1 Introduction -- 11.2 Background in Phylogenetics -- 11.3 Challenges and Opportunities for Evolutionary Computation -- 11.4 One Contribution of Evolutionary Computation: Graphyl -- 11.5 Some Other Contributions of Evolutionary computation -- 11.6 Open Questions and Opportunities -- Part Four Medicine -- 12. Evolutionary Algorithms for Cancer Chemotherapy Optimization (John McCall, Andrei Petrovski, and Siddhartha Shakya) -- 12.1 Introduction -- 12.2 Nature of Cancer -- 12.3 Nature of Chemotherapy -- 12.4 Models of Tumor Growth and Response -- 12.5 Constraints on Chemotherapy -- 12.6 Optimal Control Formulations of Cancer Chemotherapy -- 12.7 Evolutionary Algorithms for Cancer Chemotherapy Optimization -- 12.8 Encoding and Evaluation -- 12.9 Applications of EAs to Chemotherapy Optimization Problems -- 12.10 Related Work -- 12.11 Oncology Workbench -- 12.12 Conclusion -- 13. Fuzzy Ontology-Based Text Mining System for Knowledge Acquisition, Ontology Enhancement, and Query Answering from Biomedical Texts (Lipika Dey and Muhammad Abulaish). 13.1 Introduction -- 13.2 Brief Introduction to Ontologies -- 13.3 Information Retrieval form Biological Text Documents: Related Work -- 13.4 Ontology-Based IE and Knowledge Enhancement System -- 13.5 Document Processor -- 13.6 Biological Relation Extractor -- 13.7 Relation-Based Query Answering -- 13.8 Evaluation of the Biological Relation Extraction Process -- 13.9 Biological Relation Characterizer -- 13.10 Determining Strengths of Generic Biological Relations -- 13.11 Enhancing GENIA to Fuzzy Relational Ontology -- 13.12 Conclusions and Future Work -- References -- Appendix Feasible Biological Relations -- Index. |
| Record Nr. | UNINA-9910876976303321 |
| New York, : Wiley-IEEE, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computational intelligence in bioinformatics / edited by Gary B. Fogel, David W. Corne and Yi Pan
| Computational intelligence in bioinformatics / edited by Gary B. Fogel, David W. Corne and Yi Pan |
| Pubbl/distr/stampa | [Hoboken, New Jersey] : , : Wiley-IEEE, 2007 |
| Descrizione fisica | 1 online resource (377 p.) |
| Disciplina |
572.028563
572.80285 |
| Altri autori (Persone) |
CorneDavid
PanYi FogelGary <1968-> |
| Collana | IEEE press series on computational intelligence |
| Soggetto topico |
Bioinformática
Inteligencia computacional |
| Soggetto genere / forma | Libros electrónicos |
| Soggetto non controllato | Informática general |
| ISBN |
0-470-65215-2
1-281-22169-4 9786611221690 0-470-19909-1 0-470-19908-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Preface -- Contributors -- Part One Gene Expression Analysis and Systems Biology -- 1. Hybrid of Neural Classifi er and Swarm Intelligence in Multiclass Cancer Diagnosis with Gene Expression Signatures (Rui Xu, Georgios C. Anagnostopoulos, and Donald C. Wunsch II) -- 1.1 Introduction -- 1.2 Methods and Systems -- 1.3 Experimental Results -- 1.4 Conclusions -- 2. Classifying Gene Expression Profi les with Evolutionary Computation (Jin-Hyuk Hong and Sung-Bae Cho) -- 2.1 DNA Microarray Data Classifi cation -- 2.2 Evolutionary Approach to the Problem -- 2.3 Gene Selection with Speciated Genetic Algorithm -- 2.4 Cancer Classifi ction Based on Ensemble Genetic Programming -- 2.5 Conclusion -- 3. Finding Clusters in Gene Expression Data Using EvoCluster (Patrick C. H. Ma, Keith C. C. Chan, and Xin Yao) -- 3.1 Introduction -- 3.2 Related Work -- 3.3 Evolutionary Clustering Algorithm -- 3.4 Experimental Results -- 3.5 Conclusions -- 4. Gene Networks and Evolutionary Computation (Jennifer Hallinan) -- 4.1 Introduction -- 4.2 Evolutionary Optimization -- 4.3 Computational Network Modeling -- 4.4 Extending Reach of Gene Networks -- 4.5 Network Topology Analysis -- 4.6 Summary -- Part Two Sequence Analysis and Feature Detection -- 5. Fuzzy-Granular Methods for Identifying Marker Genes from Microarray Expression Data (Yuanchen He, Yuchun Tang, Yan-Qing Zhang, and Rajshekhar Sunderraman) -- 5.1 Introduction -- 5.2 Traditional Algorithms for Gene Selection -- 5.3 New Fuzzy-Granular-Based Algorithm for Gene Selection -- 5.4 Simulation -- 5.5 Conclusions -- 6. Evolutionary Feature Selection for Bioinformatics (Laetitia Jourdan, Clarisse Dhaenens, and El-Ghazali Talbi) -- 6.1 Introduction -- 6.2 Evolutionary Algorithms for Feature Selection -- 6.3 Feature Selection for Clustering in Bioinformatics -- 6.4 Feature Selection for Classifi cation in Bioinformatics -- 6.5 Frameworks and Data Sets -- 6.6 Conclusion -- 7. Fuzzy Approaches for the Analysis CpG Island Methylation Patterns (Ozy Sjahputera, Mihail Popescu, James M. Keller, and Charles W. Caldwell).
7.1 Introduction -- 7.2 Methods -- 7.3 Biological Signifi cance -- 7.4 Conclusions -- Part Three Molecular Structure and Phylogenetics -- 8. Protein-Ligand Docking with Evolutionary Algorithms(Rene Thomsen) -- 8.1 Introduction -- 8.2 Biochemical Background -- 8.3 The Docking Problem -- 8.4 Protein-Ligand Docking Algorithms -- 8.5 Evolutionary Algorithms -- 8.6 Effect of Variation Operators -- 8.7 Differential Evolution -- 8.8 Evaluating Docking Methods -- 8.9 Comparison between Docking Methods -- 8.10 Summary -- 8.11 Future Research Topics -- 9. RNA Secondary Structure Prediction Employing Evolutionary Algorithms (Kay C. Wiese, Alain A. Deschanes, and Andrew G. Hendriks) -- 9.1 Introduction -- 9.2 Thermodynamic Models -- 9.3 Methods -- 9.4 Results -- 9.5 Conclusion -- 10. Machine Learning Approach for Prediction of Human Mitochondrial Proteins (Zhong Huang, Xuheng Xu, and Xiaohua Hu) -- 10.1 Introduction -- 10.2 Methods and Systems -- 10.3 Results and Discussion -- 10.4 Conclusions -- 11. Phylogenetic Inference Using Evolutionary Algorithms(Clare Bates Congdon) -- 11.1 Introduction -- 11.2 Background in Phylogenetics -- 11.3 Challenges and Opportunities for Evolutionary Computation -- 11.4 One Contribution of Evolutionary Computation: Graphyl -- 11.5 Some Other Contributions of Evolutionary computation -- 11.6 Open Questions and Opportunities -- Part Four Medicine -- 12. Evolutionary Algorithms for Cancer Chemotherapy Optimization (John McCall, Andrei Petrovski, and Siddhartha Shakya) -- 12.1 Introduction -- 12.2 Nature of Cancer -- 12.3 Nature of Chemotherapy -- 12.4 Models of Tumor Growth and Response -- 12.5 Constraints on Chemotherapy -- 12.6 Optimal Control Formulations of Cancer Chemotherapy -- 12.7 Evolutionary Algorithms for Cancer Chemotherapy Optimization -- 12.8 Encoding and Evaluation -- 12.9 Applications of EAs to Chemotherapy Optimization Problems -- 12.10 Related Work -- 12.11 Oncology Workbench -- 12.12 Conclusion -- 13. Fuzzy Ontology-Based Text Mining System for Knowledge Acquisition, Ontology Enhancement, and Query Answering from Biomedical Texts (Lipika Dey and Muhammad Abulaish). 13.1 Introduction -- 13.2 Brief Introduction to Ontologies -- 13.3 Information Retrieval form Biological Text Documents: Related Work -- 13.4 Ontology-Based IE and Knowledge Enhancement System -- 13.5 Document Processor -- 13.6 Biological Relation Extractor -- 13.7 Relation-Based Query Answering -- 13.8 Evaluation of the Biological Relation Extraction Process -- 13.9 Biological Relation Characterizer -- 13.10 Determining Strengths of Generic Biological Relations -- 13.11 Enhancing GENIA to Fuzzy Relational Ontology -- 13.12 Conclusions and Future Work -- References -- Appendix Feasible Biological Relations -- Index. |
| Record Nr. | UNINA-9910144575003321 |
| [Hoboken, New Jersey] : , : Wiley-IEEE, 2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computational intelligence in bioinformatics / edited by Gary B. Fogel, David W. Corne and Yi Pan
| Computational intelligence in bioinformatics / edited by Gary B. Fogel, David W. Corne and Yi Pan |
| Pubbl/distr/stampa | [Hoboken, New Jersey] : , : Wiley-IEEE, 2007 |
| Descrizione fisica | 1 online resource (377 p.) |
| Disciplina |
572.028563
572.80285 |
| Altri autori (Persone) |
CorneDavid
PanYi FogelGary <1968-> |
| Collana | IEEE press series on computational intelligence |
| Soggetto topico |
Bioinformática
Inteligencia computacional |
| Soggetto genere / forma | Libros electrónicos |
| Soggetto non controllato | Informática general |
| ISBN |
0-470-65215-2
1-281-22169-4 9786611221690 0-470-19909-1 0-470-19908-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Preface -- Contributors -- Part One Gene Expression Analysis and Systems Biology -- 1. Hybrid of Neural Classifi er and Swarm Intelligence in Multiclass Cancer Diagnosis with Gene Expression Signatures (Rui Xu, Georgios C. Anagnostopoulos, and Donald C. Wunsch II) -- 1.1 Introduction -- 1.2 Methods and Systems -- 1.3 Experimental Results -- 1.4 Conclusions -- 2. Classifying Gene Expression Profi les with Evolutionary Computation (Jin-Hyuk Hong and Sung-Bae Cho) -- 2.1 DNA Microarray Data Classifi cation -- 2.2 Evolutionary Approach to the Problem -- 2.3 Gene Selection with Speciated Genetic Algorithm -- 2.4 Cancer Classifi ction Based on Ensemble Genetic Programming -- 2.5 Conclusion -- 3. Finding Clusters in Gene Expression Data Using EvoCluster (Patrick C. H. Ma, Keith C. C. Chan, and Xin Yao) -- 3.1 Introduction -- 3.2 Related Work -- 3.3 Evolutionary Clustering Algorithm -- 3.4 Experimental Results -- 3.5 Conclusions -- 4. Gene Networks and Evolutionary Computation (Jennifer Hallinan) -- 4.1 Introduction -- 4.2 Evolutionary Optimization -- 4.3 Computational Network Modeling -- 4.4 Extending Reach of Gene Networks -- 4.5 Network Topology Analysis -- 4.6 Summary -- Part Two Sequence Analysis and Feature Detection -- 5. Fuzzy-Granular Methods for Identifying Marker Genes from Microarray Expression Data (Yuanchen He, Yuchun Tang, Yan-Qing Zhang, and Rajshekhar Sunderraman) -- 5.1 Introduction -- 5.2 Traditional Algorithms for Gene Selection -- 5.3 New Fuzzy-Granular-Based Algorithm for Gene Selection -- 5.4 Simulation -- 5.5 Conclusions -- 6. Evolutionary Feature Selection for Bioinformatics (Laetitia Jourdan, Clarisse Dhaenens, and El-Ghazali Talbi) -- 6.1 Introduction -- 6.2 Evolutionary Algorithms for Feature Selection -- 6.3 Feature Selection for Clustering in Bioinformatics -- 6.4 Feature Selection for Classifi cation in Bioinformatics -- 6.5 Frameworks and Data Sets -- 6.6 Conclusion -- 7. Fuzzy Approaches for the Analysis CpG Island Methylation Patterns (Ozy Sjahputera, Mihail Popescu, James M. Keller, and Charles W. Caldwell).
7.1 Introduction -- 7.2 Methods -- 7.3 Biological Signifi cance -- 7.4 Conclusions -- Part Three Molecular Structure and Phylogenetics -- 8. Protein-Ligand Docking with Evolutionary Algorithms(Rene Thomsen) -- 8.1 Introduction -- 8.2 Biochemical Background -- 8.3 The Docking Problem -- 8.4 Protein-Ligand Docking Algorithms -- 8.5 Evolutionary Algorithms -- 8.6 Effect of Variation Operators -- 8.7 Differential Evolution -- 8.8 Evaluating Docking Methods -- 8.9 Comparison between Docking Methods -- 8.10 Summary -- 8.11 Future Research Topics -- 9. RNA Secondary Structure Prediction Employing Evolutionary Algorithms (Kay C. Wiese, Alain A. Deschanes, and Andrew G. Hendriks) -- 9.1 Introduction -- 9.2 Thermodynamic Models -- 9.3 Methods -- 9.4 Results -- 9.5 Conclusion -- 10. Machine Learning Approach for Prediction of Human Mitochondrial Proteins (Zhong Huang, Xuheng Xu, and Xiaohua Hu) -- 10.1 Introduction -- 10.2 Methods and Systems -- 10.3 Results and Discussion -- 10.4 Conclusions -- 11. Phylogenetic Inference Using Evolutionary Algorithms(Clare Bates Congdon) -- 11.1 Introduction -- 11.2 Background in Phylogenetics -- 11.3 Challenges and Opportunities for Evolutionary Computation -- 11.4 One Contribution of Evolutionary Computation: Graphyl -- 11.5 Some Other Contributions of Evolutionary computation -- 11.6 Open Questions and Opportunities -- Part Four Medicine -- 12. Evolutionary Algorithms for Cancer Chemotherapy Optimization (John McCall, Andrei Petrovski, and Siddhartha Shakya) -- 12.1 Introduction -- 12.2 Nature of Cancer -- 12.3 Nature of Chemotherapy -- 12.4 Models of Tumor Growth and Response -- 12.5 Constraints on Chemotherapy -- 12.6 Optimal Control Formulations of Cancer Chemotherapy -- 12.7 Evolutionary Algorithms for Cancer Chemotherapy Optimization -- 12.8 Encoding and Evaluation -- 12.9 Applications of EAs to Chemotherapy Optimization Problems -- 12.10 Related Work -- 12.11 Oncology Workbench -- 12.12 Conclusion -- 13. Fuzzy Ontology-Based Text Mining System for Knowledge Acquisition, Ontology Enhancement, and Query Answering from Biomedical Texts (Lipika Dey and Muhammad Abulaish). 13.1 Introduction -- 13.2 Brief Introduction to Ontologies -- 13.3 Information Retrieval form Biological Text Documents: Related Work -- 13.4 Ontology-Based IE and Knowledge Enhancement System -- 13.5 Document Processor -- 13.6 Biological Relation Extractor -- 13.7 Relation-Based Query Answering -- 13.8 Evaluation of the Biological Relation Extraction Process -- 13.9 Biological Relation Characterizer -- 13.10 Determining Strengths of Generic Biological Relations -- 13.11 Enhancing GENIA to Fuzzy Relational Ontology -- 13.12 Conclusions and Future Work -- References -- Appendix Feasible Biological Relations -- Index. |
| Record Nr. | UNINA-9910829979903321 |
| [Hoboken, New Jersey] : , : Wiley-IEEE, 2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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