| Description |
1 online resource (290 pages) |
| Contents |
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 M2M in 5G Cellular Networks: Challenges, Proposed Solutions, and Future Directions -- 1.1 Introduction -- 1.2 Literature Survey -- 1.3 Survey Challenges and Proposed Solutions of M2M -- 1.3.1 PARCH Overload Problem -- 1.3.2 Inefficient Radio Resource Utilization and Allocation -- 1.3.3 M2M Random Access Challenges -- 1.3.4 Clustering Techniques -- 1.3.5 QoS Provisioning for M2M Communications -- 1.3.6 Less Cost and Low Power Device Requirements -- 1.3.7 Security and Privacy -- 1.4 Conclusion -- References -- Chapter 2 MAC Layer Protocol for Wireless Security -- 2.1 Introduction -- 2.2 MAC Layer -- 2.2.1 Centralized Control -- 2.2.2 Deterministic Access -- 2.2.3 Non-Deterministic Access -- 2.3 Functions of the MAC Layer -- 2.4 MAC Layer Protocol -- 2.4.1 Random Access Protocol -- 2.4.2 Controlled Access Protocols -- 2.4.3 Channelization -- 2.5 MAC Address -- 2.6 Conclusion and Future Scope -- References -- Chapter 3 Enhanced Image Security Through Hybrid Approach: Protect Your Copyright Over Digital Images -- 3.1 Introduction -- 3.2 Literature Review -- 3.3 Design Issues -- 3.3.1 Robustness Against Various Attack Conditions -- 3.3.2 Distortion and Visual Quality -- 3.3.3 Working Domain -- 3.3.4 Human Visual System (HVS) -- 3.3.5 The Trade-Off between Robustness and Imperceptibility -- 3.3.6 Computational Cost -- 3.4 A Secure Grayscale Image Watermarking Based on DWT-SVD -- 3.5 Experimental Results -- 3.6 Conclusion -- References -- Chapter 4 Quantum Computing -- 4.1 Introduction -- 4.2 A Brief History of Quantum Computing -- 4.3 Postulate of Quantum Mechanics -- 4.4 Polarization and Entanglement -- 4.5 Applications and Advancements -- 4.5.1 Cryptography, Teleportation and Communication Networks -- 4.5.2 Quantum Computing and Memories |
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4.5.3 Satellite Communication Based on Quantum Computing -- 4.5.4 Machine Learning & -- Artificial Intelligence -- 4.6 Optical Quantum Computing -- 4.7 Experimental Realisation of Quantum Computer -- 4.7.1 Hetero-Polymers -- 4.7.2 Ion Traps -- 4.7.3 Quantum Electrodynamics Cavity -- 4.7.4 Quantum Dots -- 4.8 Challenges of Quantum Computing -- 4.9 Conclusion and Future Scope -- References -- Chapter 5 Feature Engineering for Flow-Based IDS -- 5.1 Introduction -- 5.1.1 Intrusion Detection System -- 5.1.2 IDS Classification -- 5.2 IP Flows -- 5.2.1 The Architecture of Flow-Based IDS -- 5.2.2 Wireless IDS Designed Using Flow-Based Approach -- 5.2.3 Comparison of Flow- and Packet-Based IDS -- 5.3 Feature Engineering -- 5.3.1 Curse of Dimensionality -- 5.3.2 Feature Selection -- 5.3.3 Feature Categorization -- 5.4 Classification of Feature Selection Technique -- 5.4.1 The Wrapper, Filter, and Embedded Feature Selection -- 5.4.2 Correlation, Consistency, and PCA-Based Feature Selection -- 5.4.3 Similarity, Information Theoretical, Sparse Learning, and Statistical-Based Feature Selection -- 5.4.4 Univariate and Multivariate Feature Selection -- 5.5 Tools and Library for Feature Selection -- 5.6 Literature Review on Feature Selection in Flow-Based IDS -- 5.7 Challenges and Future Scope -- 5.8 Conclusions -- Acknowledgement -- References -- Chapter 6 Environmental Aware Thermal (EAT) Routing Protocol for Wireless Sensor Networks -- 6.1 Introduction -- 6.1.1 Single Path Routing Protocol -- 6.1.2 Multipath Routing Protocol -- 6.1.3 Environmental Influence on WSN -- 6.2 Motivation Behind the Work -- 6.3 Novelty of This Work -- 6.4 Related Works -- 6.5 Proposed Environmental Aware Thermal (EAT) Routing Protocol -- 6.5.1 Sensor Node Environmental Modeling and Analysis -- 6.5.2 Single Node Environmental Influence Modeling -- 6.5.3 Multiple Node Modeling |
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6.5.4 Sensor Node Surrounding Temperature Field -- 6.5.5 Sensor Node Remaining Energy Calculation -- 6.5.6 Delay Modeling -- 6.6 Simulation Parameters -- 6.7 Results and Discussion -- 6.7.1 Temperature Influence on Network -- 6.7.2 Power Consumption -- 6.7.3 Lifetime Analysis -- 6.7.4 Delay Analysis -- 6.8 Conclusion -- References -- Chapter 7 A Comprehensive Study of Intrusion Detection and Prevention Systems -- 7.1 Introduction -- 7.1.1 Intrusion and Detection -- 7.1.2 Some Basic Definitions -- 7.1.3 Intrusion Detection and Prevention System -- 7.1.4 Need for IDPS: More Than Ever -- 7.1.5 Introduction to Alarms -- 7.1.6 Components of an IDPS -- 7.2 Configuring IDPS -- 7.2.1 Network Architecture of IDPS -- 7.2.2 A Glance at Common Types -- 7.2.2.1 Network-Based IDS -- 7.2.2.2 Host-Based IDS -- 7.2.3 Intrusion Detection Techniques -- 7.2.3.1 Conventional Techniques -- 7.2.3.2 Machine Learning-Based and Hybrid Techniques -- 7.2.4 Three Considerations -- 7.2.4.1 Location of Sensors -- 7.2.4.2 Security Capabilities -- 7.2.4.3 Management Capabilities -- 7.2.5 Administrators' Functions -- 7.2.5.1 Deployment -- 7.2.5.2 Testing -- 7.2.5.3 Security Consideration of IDPS -- 7.2.5.4 Regular Backups and Monitoring -- 7.2.6 Types of Events Detected -- 7.2.7 Role of State in Network Security -- 7.3 Literature Review -- 7.4 Conclusion -- References -- Chapter 8 Hardware Devices Integration With IoT -- 8.1 Introduction -- 8.2 Literature Review -- 8.3 Component Description -- 8.3.1 Arduino Board UNO -- 8.3.2 Raspberry Pi -- 8.4 Case Studies -- 8.4.1 Ultrasonic Sensor -- 8.4.2 Temperature and Humidity Sensor -- 8.4.3 Weather Monitoring System Using Raspberry Pi -- 8.5 Drawbacks of Arduino and Raspberry Pi -- 8.6 Challenges in IoT -- 8.6.1 Design Challenges -- 8.6.2 Security Challenges -- 8.6.3 Development Challenges -- 8.7 Conclusion -- 8.8 Annexures -- References |
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Additional Resources -- Chapter 9 Depth Analysis On DoS & -- DDoS Attacks -- 9.1 Introduction -- 9.1.1 Objective and Motivation -- 9.1.2 Symptoms and Manifestations -- 9.2 Literature Survey -- 9.3 Timeline of DoS and DDoS Attacks -- 9.4 Evolution of Denial of Service (DoS) & -- Distributed Denial of Service (DDoS) -- 9.5 DDoS Attacks: A Taxonomic Classification -- 9.5.1 Classification Based on Degree of Automation -- 9.5.2 Classification Based on Exploited Vulnerability -- 9.5.3 Classification Based on Rate Dynamics of Attacks -- 9.5.4 Classification Based on Impact -- 9.6 Transmission Control Protocol -- 9.6.1 TCP Three-Way Handshake -- 9.7 User Datagram Protocol -- 9.7.1 UDP Header -- 9.8 Types of DDoS Attacks -- 9.8.1 TCP SYN Flooding Attack -- 9.8.2 UDP Flooding Attack -- 9.8.3 Smurf Attack -- 9.8.4 Ping of Death Attack -- 9.8.5 HTTP Flooding Attack -- 9.9 Impact of DoS/DDoS on Various Areas -- 9.9.1 DoS/DDoS Attacks on VoIP Networks Using SIP -- 9.9.2 DoS/DDoS Attacks on VANET -- 9.9.3 DoS/DDoS Attacks on Smart Grid System -- 9.9.4 DoS/DDoS Attacks in IoT-Based Devices -- 9.10 Countermeasures to DDoS Attack -- 9.10.1 Prevent Being Agent/Secondary Target -- 9.10.2 Detect and Neutralize Attacker -- 9.10.3 Potential Threats Detection/Prevention -- 9.10.4 DDoS Attacks and How to Avoid Them -- 9.10.5 Deflect Attack -- 9.10.6 Post-Attack Forensics -- 9.11 Conclusion -- 9.12 Future Scope -- References -- Chapter 10 SQL Injection Attack on Database System -- 10.1 Introduction -- 10.1.1 Types of Vulnerabilities -- 10.1.2 Types of SQL Injection Attack -- 10.1.3 Impact of SQL Injection Attack -- 10.2 Objective and Motivation -- 10.3 Process of SQL Injection Attack -- 10.4 Related Work -- 10.5 Literature Review -- 10.6 Implementation of the SQL Injection Attack -- 10.6.1 Access the Database Using the 1=1 SQL Injection Statement |
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10.6.2 Access the Database Using the ""='''' SQL Injection Statement -- 10.6.3 Access and Upgrade the Database by Using Batch SQL Injection Statement -- 10.7 Detection of SQL Injection Attack -- 10.8 Prevention/Mitigation from SQL Injection Attack -- 10.9 Conclusion -- References -- Chapter 11 Machine Learning Techniques for Face Authentication System for Security Purposes -- 11.1 Introduction -- 11.2 Face Recognition System (FRS) in Security -- 11.3 Theory -- 11.3.1 Neural Networks -- 11.3.2 Convolutional Neural Network (CNN) -- 11.3.3 K-Nearest Neighbors (KNN) -- 11.3.4 Support Vector Machine (SVM) -- 11.3.5 Logistic Regression (LR) -- 11.3.6 Naive Bayes (NB) -- 11.3.7 Decision Tree (DT) -- 11.4 Experimental Methodology -- 11.4.1 Dataset -- 11.4.2 Convolutional Neural Network (CNN) -- 11.4.3 Other Machine Learning Techniques -- 11.5 Results -- 11.6 Conclusion -- References -- Chapter 12 Estimation of Computation Time for Software-Defined Networking-Based Data Traffic Offloading System in Heterogeneous Network -- 12.1 Introduction -- 12.1.1 Motivation -- 12.1.2 Objective -- 12.1.3 The Main Contributions of This Chapter -- 12.2 Analysis of SDN-TOS Mechanism -- 12.2.1 Key Components of SDN-TOS -- 12.2.2 LTE/Wi-Fi in a Heterogeneous Network (HetNet) -- 12.2.3 Centralized SDN Controller -- 12.2.4 Key Design Considerations of SDN-TOS -- 12.2.4.1 The System Architecture -- 12.2.4.2 Mininet Wi-Fi Emulated Networks -- 12.2.4.3 Software-Defined Networking Controller -- 12.3 Materials and Methods -- 12.3.1 Estimating Time Consumption for Mininet Wi-Fi Emulator -- 12.3.1.1 Total Time Consumption for Offloading the Data Traffic by Service Provider -- 12.3.1.2 Total Time Consumption of Mininet Wi-Fi Emulator (Time Consumption for Both LTE and Wi-Fi Network) -- 12.3.2 Estimating Time Consumption for SDN Controller |
| Summary |
Presenting the concepts and advances of wireless communication security, this volume, written and edited by a global team of experts, also goes into the practical applications for the engineer, student, and other industry professionals. -- Edited summary from book |
| Notes |
12.3.2.1 Total Response Time for Sub-Controller |
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Description based on publisher supplied metadata and other sources |
| Subject |
Wireless sensor networks.
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Wireless sensor networks
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| Form |
Electronic book
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| Author |
Bharti, Manisha
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Niranjanamurthy, M
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| ISBN |
1119777461 |
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9781119777465 |
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1119777453 |
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9781119777458 |
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