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Submit a ProposalWireless Communication Security
 | Mobile and Network Security Protocols Edited by Manju Khari, Manisha Bharti, and M. Niranjanamurthy Series: Advances in Data Engineering and Machine Learning Copyright: 2023 | Status: Published ISBN: 9781119777144 | Hardcover | 251 pages Price: $225 USD  |
One Line Description
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.
Audience
Researchers, software developers, engineers, scientists, students, and other professionals in communication engineering, electronics, electrical engineering, and other areas of research
Researchers, software developers, engineers, scientists, students, and other professionals in communication engineering, electronics, electrical engineering, and other areas of research
Description
Covering a broad range of topics in wireless communication security and its solutions, this outstanding new volume is of great interest to engineers, scientists, and students from a variety of backgrounds and interests, thereby allowing considerable flexibility in making up the course material for researchers and academicians. Focusing on providing the theory of wireless communication within the framework of its practical applications, the contributors take on a wealth of topics, integrating seemingly diverse areas under one cover.
Wireless Communication Security has been divided into five units. The first unit presents the different protocols and standards for developing a real-time wireless communication security. The second unit presents different widely accepted networks, which are the core of wireless communication security. Unit three presents the various device and network controlling methodologies. Unit 4 presents the various high performance and computationally efficient algorithms for efficient and scalable implementation of network protocols, and the last unit presents the leading innovations and variety of usage of wireless communication security. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in these areas, this is a must-have for any library.
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Covering a broad range of topics in wireless communication security and its solutions, this outstanding new volume is of great interest to engineers, scientists, and students from a variety of backgrounds and interests, thereby allowing considerable flexibility in making up the course material for researchers and academicians. Focusing on providing the theory of wireless communication within the framework of its practical applications, the contributors take on a wealth of topics, integrating seemingly diverse areas under one cover.
Wireless Communication Security has been divided into five units. The first unit presents the different protocols and standards for developing a real-time wireless communication security. The second unit presents different widely accepted networks, which are the core of wireless communication security. Unit three presents the various device and network controlling methodologies. Unit 4 presents the various high performance and computationally efficient algorithms for efficient and scalable implementation of network protocols, and the last unit presents the leading innovations and variety of usage of wireless communication security. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in these areas, this is a must-have for any library.
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Author / Editor Details
Manju Khari, PhD, is an assistant professor in AIACTR, affiliated with GGSIP University, Delhi, India. She is also the professor-in-charge of the IT Services of the Institute and has experience of more than twelve years in network planning and management. She holds a PhD in computer science and engineering from the National Institute of Technology, Patna.
Manju Khari, PhD, is an assistant professor in AIACTR, affiliated with GGSIP University, Delhi, India. She is also the professor-in-charge of the IT Services of the Institute and has experience of more than twelve years in network planning and management. She holds a PhD in computer science and engineering from the National Institute of Technology, Patna.
Manisha Bharti, PhD, is an assistant professor at the National Institute of Technology (NIT) Delhi, India. She received her PhD from IKG Punjab Technical University, Jalandhar and has over 12 years of teaching and research experience.
M. Niranjanamurthy, PhD, is an assistant professor in the Department of Artificial Intelligence and Machine Learning, B.M.S. Institute of Technology and Management, Yalahanka, Bangalore, Karnataka. He earned his PhD in computer science at JJTU. He has over 10 years of teaching experience and two years of industry experience as a software engineer. He has two patents to his credit and has won numerous awards. He has published four books, and he is currently working on numerous books for Scrivener Publishing. He has also published over 50 papers in scholarly journals.
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Table of Contents
Preface
1. M2M in 5G Cellular Networks: Challenges, Proposed Solutions, and Future Directions
Kiran Ahuja and Indu Bala
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
2. MAC Layer Protocol for Wireless Security
Sushmita Kumari and Manisha Bharti
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
3. Enhanced Image Security Through Hybrid Approach: Protect Your Copyright Over Digital Images
Shaifali M. Arora and Poonam Kadian
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
4. Quantum Computing
Manisha Bharti and Tanvika Garg
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
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
5. Feature Engineering for Flow-Based IDS
Rahul B. Adhao and Vinod K. Pachghare
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
6. Environmental Aware Thermal (EAT) Routing Protocol for Wireless Sensor Networks
B. Banuselvasaraswathy and Vimalathithan Rathinasabapathy
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
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
7. A Comprehensive Study of Intrusion Detection and Prevention Systems
Bhoopesh Singh Bhati, Dikshita, Nitesh Singh Bhati and Garvit Chugh
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
8. Hardware Devices Integration With IoT
Sushant Kumar and Saurabh Mukherjee
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
Additional Resources
9. Depth Analysis On DoS & DDoS Attacks
Gaurav Nayak, Anjana Mishra, Uditman Samal and Brojo Kishore Mishra
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
10. SQL Injection Attack on Database System
Mohit Kumar
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
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
11. Machine Learning Techniques for Face Authentication System for Security Purposes
Vibhuti Jain, Madhavendra Singh and Jagannath Jayanti
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
12. Estimation of Computation Time for Software-Defined Networking-Based Data Traffic Offloading System in Heterogeneous Network
Shashila S. Abayagunawardhana, Malka N. Halgamuge and Charitha Subhashi Jayasekara
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
12.3.2.1 Total Response Time for Sub-Controller
12.3.2.2 Total Response Time for The Total Process of Centralized SDN Controller
12.3.3 Estimating Total Time Consumption for SDN-Based Traffic Offloading System (SDN-TOS)
12.4 Simulation Results
12.4.1 Effect of Computational Data Traffic θI on Total Response Time (TA)/Service Provider A and CSP Approach
12.4.2 Effect of Computational Data Traffic θI on Total Response Time (TA) for Different Service Providers/Service Provider A and Service Provider B
12.5 Discussion
12.6 Conclusion
References
About the Editors
Index
Back to Top
Preface
1. M2M in 5G Cellular Networks: Challenges, Proposed Solutions, and Future Directions
Kiran Ahuja and Indu Bala
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
2. MAC Layer Protocol for Wireless Security
Sushmita Kumari and Manisha Bharti
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
3. Enhanced Image Security Through Hybrid Approach: Protect Your Copyright Over Digital Images
Shaifali M. Arora and Poonam Kadian
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
4. Quantum Computing
Manisha Bharti and Tanvika Garg
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
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
5. Feature Engineering for Flow-Based IDS
Rahul B. Adhao and Vinod K. Pachghare
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
6. Environmental Aware Thermal (EAT) Routing Protocol for Wireless Sensor Networks
B. Banuselvasaraswathy and Vimalathithan Rathinasabapathy
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
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
7. A Comprehensive Study of Intrusion Detection and Prevention Systems
Bhoopesh Singh Bhati, Dikshita, Nitesh Singh Bhati and Garvit Chugh
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
8. Hardware Devices Integration With IoT
Sushant Kumar and Saurabh Mukherjee
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
Additional Resources
9. Depth Analysis On DoS & DDoS Attacks
Gaurav Nayak, Anjana Mishra, Uditman Samal and Brojo Kishore Mishra
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
10. SQL Injection Attack on Database System
Mohit Kumar
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
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
11. Machine Learning Techniques for Face Authentication System for Security Purposes
Vibhuti Jain, Madhavendra Singh and Jagannath Jayanti
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
12. Estimation of Computation Time for Software-Defined Networking-Based Data Traffic Offloading System in Heterogeneous Network
Shashila S. Abayagunawardhana, Malka N. Halgamuge and Charitha Subhashi Jayasekara
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
12.3.2.1 Total Response Time for Sub-Controller
12.3.2.2 Total Response Time for The Total Process of Centralized SDN Controller
12.3.3 Estimating Total Time Consumption for SDN-Based Traffic Offloading System (SDN-TOS)
12.4 Simulation Results
12.4.1 Effect of Computational Data Traffic θI on Total Response Time (TA)/Service Provider A and CSP Approach
12.4.2 Effect of Computational Data Traffic θI on Total Response Time (TA) for Different Service Providers/Service Provider A and Service Provider B
12.5 Discussion
12.6 Conclusion
References
About the Editors
Index
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