Wireless Communication Security
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.
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. 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 four 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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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 Computer Applications, M S Ramaiah Institute of Technology, 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.
Content
Preface xiii
1 M2M in 5G Cellular Networks: Challenges, Proposed Solutions, and Future Directions 1
Kiran Ahuja and Indu Bala
1.1 Introduction 2
1.2 Literature Survey 5
1.3 Survey Challenges and Proposed Solutions of M2M 7
1.3.1 PARCH Overload Problem 8
1.3.2 Inefficient Radio Resource Utilization and Allocation 10
1.3.3 M2M Random Access Challenges 12
1.3.4 Clustering Techniques 13
1.3.5 QoS Provisioning for M2M Communications 15
1.3.6 Less Cost and Low Power Device Requirements 16
1.3.7 Security and Privacy 17
1.4 Conclusion 18
References 19
2 MAC Layer Protocol for Wireless Security 23
Sushmita Kumari and Manisha Bharti
2.1 Introduction 23
2.2 MAC Layer 24
2.2.1 Centralized Control 24
2.2.2 Deterministic Access 24
2.2.3 Non-Deterministic Access 24
2.3 Functions of the MAC Layer 25
2.4 MAC Layer Protocol 25
2.4.1 Random Access Protocol 26
2.4.2 Controlled Access Protocols 29
2.4.3 Channelization 31
2.5 MAC Address 31
2.6 Conclusion and Future Scope 33
References 33
3 Enhanced Image Security Through Hybrid Approach: Protect Your Copyright Over Digital Images 35
Shaifali M. Arora and Poonam Kadian
3.1 Introduction 36
3.2 Literature Review 38
3.3 Design Issues 40
3.3.1 Robustness Against Various Attack Conditions 40
3.3.2 Distortion and Visual Quality 41
3.3.3 Working Domain 42
3.3.4 Human Visual System (HVS) 43
3.3.5 The Trade-Off between Robustness and Imperceptibility 43
3.3.6 Computational Cost 43
3.4 A Secure Grayscale Image Watermarking Based on DWT-SVD 43
3.5 Experimental Results 45
3.6 Conclusion 52
References 52
4 Quantum Computing 59
Manisha Bharti and Tanvika Garg
4.1 Introduction 59
4.2 A Brief History of Quantum Computing 60
4.3 Postulate of Quantum Mechanics 61
4.4 Polarization and Entanglement 61
4.5 Applications and Advancements 63
4.5.1 Cryptography, Teleportation and Communication Networks 63
4.5.2 Quantum Computing and Memories 63
4.5.3 Satellite Communication Based on Quantum Computing 64
4.5.4 Machine Learning & Artificial Intelligence 65
4.6 Optical Quantum Computing 65
4.7 Experimental Realisation of Quantum Computer 66
4.7.1 Hetero-Polymers 66
4.7.2 Ion Traps 67
4.7.3 Quantum Electrodynamics Cavity 67
4.7.4 Quantum Dots 67
4.8 Challenges of Quantum Computing 67
4.9 Conclusion and Future Scope 68
References 68
5 Feature Engineering for Flow-Based IDS 69
Rahul B. Adhao and Vinod K. Pachghare
5.1 Introduction 70
5.1.1 Intrusion Detection System 71
5.1.2 IDS Classification 71
5.2 IP Flows 72
5.2.1 The Architecture of Flow-Based IDS 73
5.2.2 Wireless IDS Designed Using Flow-Based Approach 73
5.2.3 Comparison of Flow- and Packet-Based IDS 74
5.3 Feature Engineering 75
5.3.1 Curse of Dimensionality 76
5.3.2 Feature Selection 78
5.3.3 Feature Categorization 78
5.4 Classification of Feature Selection Technique 78
5.4.1 The Wrapper, Filter, and Embedded Feature Selection 78
5.4.2 Correlation, Consistency, and PCA-Based Feature Selection 80
5.4.3 Similarity, Information Theoretical, Sparse Learning, and Statistical-Based Feature Selection 80
5.4.4 Univariate and Multivariate Feature Selection 81
5.5 Tools and Library for Feature Selection 82
5.6 Literature Review on Feature Selection in Flow-Based IDS 82
5.7 Challenges and Future Scope 86
5.8 Conclusions 87
Acknowledgement 87
References 88
6 Environmental Aware Thermal (EAT) Routing Protocol for Wireless Sensor Networks 91
B. Banuselvasaraswathy and Vimalathithan Rathinasabapathy
6.1 Introduction 92
6.1.1 Single Path Routing Protocol 93
6.1.2 Multipath Routing Protocol 94
6.1.3 Environmental Influence on WSN 96
6.2 Motivation Behind the Work 97
6.3 Novelty of This Work 98
6.4 Related Works 99
6.5 Proposed Environmental Aware Thermal (EAT) Routing Protocol 102
6.5.1 Sensor Node Environmental Modeling and Analysis 104
6.5.2 Single Node Environmental Influence Modeling 105
6.5.3 Multiple Node Modeling 106
6.5.4 Sensor Node Surrounding Temperature Field 106
6.5.5 Sensor Node Remaining Energy Calculation 107
6.5.6 Delay Modeling 107
6.6 Simulation Parameters 108
6.7 Results and Discussion 109
6.7.1 Temperature Influence on Network 109
6.7.2 Power Consumption 109
6.7.3 Lifetime Analysis 110
6.7.4 Delay Analysis 111
6.8 Conclusion 112
References 112
7 A Comprehensive Study of Intrusion Detection and Prevention Systems 115
Bhoopesh Singh Bhati, Dikshita, Nitesh Singh Bhati and Garvit Chugh
7.1 Introduction 116
7.1.1 Intrusion and Detection 116
7.1.2 Some Basic Definitions 116
7.1.3 Intrusion Detection and Prevention System 117
7.1.4 Need for IDPS: More Than Ever 118
7.1.5 Introduction to Alarms 118
7.1.6 Components of an IDPS 119
7.2 Configuring IDPS 120
7.2.1 Network Architecture of IDPS 120
7.2.2 A Glance at Common Types 121
7.2.2.1 Network-Based IDS 123
7.2.2.2 Host-Based IDS 124
7.2.3 Intrusion Detection Techniques 125
7.2.3.1 Conventional Techniques 125
7.2.3.2 Machine Learning-Based and Hybrid Techniques 128
7.2.4 Three Considerations 131
7.2.4.1 Location of Sensors 131
7.2.4.2 Security Capabilities 131
7.2.4.3 Management Capabilities 133
7.2.5 Administrators' Functions 134
7.2.5.1 Deployment 134
7.2.5.2 Testing 134
7.2.5.3 Security Consideration of IDPS 135
7.2.5.4 Regular Backups and Monitoring 135
7.2.6 Types of Events Detected 135
7.2.7 Role of State in Network Security 136
7.3 Literature Review 137
7.4 Conclusion 138
References 139
8 Hardware Devices Integration With IoT 143
Sushant Kumar and Saurabh Mukherjee
8.1 Introduction 143
8.2 Literature Review 144
8.3 Component Description 146
8.3.1 Arduino Board UNO 146
8.3.2 Raspberry Pi 147
8.4 Case Studies 148
8.4.1 Ultrasonic Sensor 148
8.4.2 Temperature and Humidity Sensor 150
8.4.3 Weather Monitoring System Using Raspberry Pi 151
8.5 Drawbacks of Arduino and Raspberry Pi 153
8.6 Challenges in IoT 154
8.6.1 Design Challenges 154
8.6.2 Security Challenges 155
8.6.3 Development Challenges 155
8.7 Conclusion 155
8.8 Annexures 156
References 157
Additional Resources 158
9 Depth Analysis On DoS & DDoS Attacks 159
Gaurav Nayak, Anjana Mishra, Uditman Samal and Brojo Kishore Mishra
9.1 Introduction 160
9.1.1 Objective and Motivation 161
9.1.2 Symptoms and Manifestations 163
9.2 Literature Survey 163
9.3 Timeline of DoS and DDoS Attacks 164
9.4 Evolution of Denial of Service (DoS) & Distributed Denial of Service (DDoS) 165
9.5 DDoS Attacks: A Taxonomic Classification 166
9.5.1 Classification Based on Degree of Automation 166
9.5.2 Classification Based on Exploited Vulnerability 167
9.5.3 Classification Based on Rate Dynamics of Attacks 168
9.5.4 Classification Based on Impact 168
9.6 Transmission Control Protocol 169
9.6.1 TCP Three-Way Handshake 169
9.7 User Datagram Protocol 170
9.7.1 UDP Header 170
9.8 Types of DDoS Attacks 170
9.8.1 TCP SYN Flooding Attack 171
9.8.2 UDP Flooding Attack 172
9.8.3 Smurf Attack 172
9.8.4 Ping of Death Attack 173
9.8.5 HTTP Flooding Attack 174
9.9 Impact of DoS/DDoS on Various Areas 175
9.9.1 DoS/DDoS Attacks on VoIP Networks Using SIP 175
9.9.2 DoS/DDoS Attacks on VANET 175
9.9.3 DoS/DDoS Attacks on Smart Grid System 176
9.9.4 DoS/DDoS Attacks in IoT-Based Devices 176
9.10 Countermeasures to DDoS Attack 177
9.10.1 Prevent Being Agent/Secondary Target 177
9.10.2 Detect and Neutralize Attacker 178
9.10.3 Potential Threats Detection/Prevention 178
9.10.4 DDoS Attacks and How to Avoid Them 178
9.10.5 Deflect Attack 178
9.10.6 Post-Attack Forensics 179
9.11 Conclusion 179
9.12 Future Scope 180
References 180
10 SQL Injection Attack on Database System 183
Mohit Kumar
10.1 Introduction 183
10.1.1 Types of Vulnerabilities 184
10.1.2 Types of SQL Injection Attack 185
10.1.3 Impact of SQL Injection Attack 186
10.2 Objective and Motivation 186
10.3 Process of SQL Injection Attack 188
10.4 Related Work 188
10.5 Literature Review 189
10.6 Implementation of the SQL Injection Attack 192
10.6.1 Access the Database Using the 1=1 SQL Injection Statement 192
10.6.2 Access the Database Using the ""='''' SQL Injection Statement 193
10.6.3 Access and Upgrade the Database by Using Batch SQL Injection Statement 194
10.7 Detection of SQL Injection Attack 196
10.8 Prevention/Mitigation from SQL Injection Attack 196
10.9 Conclusion 197
References 197
11 Machine Learning Techniques for Face Authentication System for Security Purposes 199
Vibhuti Jain, Madhavendra Singh and Jagannath Jayanti
11.1 Introduction 200
11.2 Face Recognition System (FRS) in Security 201
11.3 Theory 202
11.3.1 Neural Networks 202
11.3.2 Convolutional Neural Network (CNN) 204
11.3.3 K-Nearest Neighbors (KNN) 207
11.3.4 Support Vector Machine (SVM) 208
11.3.5 Logistic Regression (LR) 209
11.3.6 Naive Bayes (NB) 210
11.3.7 Decision Tree (DT) 211
11.4 Experimental Methodology 212
11.4.1 Dataset 212
11.4.2 Convolutional Neural Network (CNN) 212
11.4.3 Other Machine Learning Techniques 215
11.5 Results 218
11.6 Conclusion 220
References 220
12 Estimation of Computation Time for Software-Defined Networking-Based Data Traffic Offloading System in Heterogeneous Network 223
Shashila S. Abayagunawardhana, Malka N. Halgamuge and Charitha Subhashi Jayasekara
12.1 Introduction 224
12.1.1 Motivation 225
12.1.2 Objective 228
12.1.3 The Main Contributions of This Chapter 228
12.2 Analysis of SDN-TOS Mechanism 229
12.2.1 Key Components of SDN-TOS 229
12.2.2 LTE/Wi-Fi in a Heterogeneous Network (HetNet) 229
12.2.3 Centralized SDN Controller 229
12.2.4 Key Design Considerations of SDN-TOS 230
12.2.4.1 The System Architecture 230
12.2.4.2 Mininet Wi-Fi Emulated Networks 230
12.2.4.3 Software-Defined Networking Controller 231
12.3 Materials and Methods 232
12.3.1 Estimating Time Consumption for Mininet Wi-Fi Emulator 232
12.3.1.1 Total Time Consumption for Offloading the Data Traffic by Service Provider 233
12.3.1.2 Total Time Consumption of Mininet Wi-Fi Emulator (Time Consumption for Both LTE and Wi-Fi Network) 236
12.3.2 Estimating Time Consumption for SDN Controller 237
12.3.2.1 Total Response Time for Sub-Controller 237
12.3.2.2 Total Response Time for The Total Process of Centralized SDN Controller 238
12.3.3 Estimating Total Time Consumption for SDN-Based Traffic Offloading System (sdn-tos) 239
12.4 Simulation Results 240
12.4.1 Effect of Computational Data Traffic ¿I on Total Response Time (TA)/Service Provider A and CSP Approach 242
12.4.2 Effect of Computational Data Traffic ¿I on Total Response Time (TA) for Different Service Providers/Service Provider A and Service Provider B 243
12.5 Discussion 244
12.6 Conclusion 246
References 247
About the Editors 253
Index 255
1
M2M in 5G Cellular Networks: Challenges, Proposed Solutions, and Future Directions
Kiran Ahuja1* and Indu Bala2
1Department of Electronics and Communication Engineering, DAV Institute of Engineering and Technology, Jalandhar, India
2School of Electronics and Electrical Engineering Lovely Professional University, Phagwara, Punjab, India
Abstract
Fifth-generation wireless networks (5G) are defined to meet the requirements of high data rates for thousands of users, synchronized connections for vast wireless sensor networks, improved coverage area, efficient signal processing, low latency and enhanced network spectrum as compared to the fourth-generation wireless networks (4G). These networks were initially envisioned for efficient and fast mobile networks along with converged fiber-wireless networks. However, with the explosion of smart devices and emerging multimedia applications the need to roll out 5G networks to meet the demands both at the consumer and business end became necessary. Therefore, to create a network with faster speed, the 5G networks have initiated a new basis for communication, which consists of the Internet of Things (IoT) and Machine-to-Machine communication (M2M). The IoT and M2M have been able to overcome the major limitations of 5G to initiate multiple-hop networks, making available high data rates to peers between several base stations and thereby reducing costs and initiating reliable security standards. Such a major deviation from the conventional design to involve large networks to support massive access by machine-type devices (MTDs) sets special technical challenges for M2M. This chapter offers an outline of the main issues raised by the M2M vision along with a survey of the common approaches proposed in the literature to enable the coexistence of M2M devices and the challenges which need to be investigated.
Keywords: Machine-to-Machine, Internet of Things (IoTs), 5G
1.1 Introduction
Every five years or so, enormous changes occur in cellular networks with the already existing generation networks in order to fix the faults of its predecessor networks. The 4G network was needed to make consuming data less of an unpleasant experience. However, it had its flaws, which were fixed by the emergence of 5G, which created a big change in the mobile networks. With the ever-growing count of wireless users, telecom technologies continued to develop speedily, supporting the growth of service capacity and coverage to fulfill user demand for higher data. But the concerning issue with current network standards is a serious lack of bandwidth which limits support of higher data networks. Due to this issue, radio spectrums on which the 4G networks operate are overcrowded and thereby are predicted to increase mobile traffic between 2010 and 2020 [1]. This being one of the major challenges, the telecom businesses are depending on 5G as an existence investor considering growing marketplace overthrow via internet groups. Attempts are being made via the telecom companies to outline 5G technological know-how that gives record transmission velocity of 10 gigabytes over the air [2], latency in the order of 1ms [3] and IoT units which run on a battery lasting for up to 10 years [4, 10].
In contrast to the 5G network, the contemporary vision of communication systems in the new business areas like car-satellite communications, home automation, health security remote controlling, smart cities, Mobile POS, etc., require complete automated communication without human intervention. Such a novel form of communication is referred to as M2M communications. M2M visualizes a scenario where equipment on both sides have tens or hundreds of antennas or even more that renders better data rates for users with efficient energy and spectrum. It serves as the key element in the emerging of Internet of Things and Smart City models [5] and [6], which are planned to provide solutions to present and upcoming socioeconomic necessities for tracking and monitoring services, as well as for novel applications and advanced business setups [7].
The basic idea of M2M is to enable direct communication between users and the devices without the occupancy of the core network elements which requires offloading of the networks thereby exploiting the physical proximities of the terminals. Even with the call for such solutions, the potential of M2M can be set free only if the connectivity of the Machine-type Devices (MTDs) is probable everywhere without employing additional devices and without (or with minimal) configuration. In this point of fact, the ideal situation should be such where the MTDs are ready to be connected with the rest of the world by placing it in the favorable position. Figure 1.1 describes the ways of connectivity in the M2M communication with three cases.
With specific instances of M2M connectivity new applications with international offerings are connecting a number of kinds of embedded Wi-Fi machines/devices to create an unexpectedly developing IoT which guarantees to expand boom and income possibilities for modern-day carriers in the facet of waning margins in hooked up strains of business. Including the IoT applications, the M2M links the networks in many ways, providing an optimal form of connectivity with the Machine-Type Communications (MTCs), enabling: faraway industrial manage structures (ICS); security metering monitoring of transportation; third-party video streaming and gaming content; voice signaling; e-healthcare emergency monitoring and metering; domestic and industrial automation and a lot more. Figure 1.2 indicates a range of functions of the M2M conversation at a variety of grounds of growing a big ad hoc network permitting close by units to connect.
Unfortunately, due to the massive accesses and high user demands the technologies that are supposed to carry out MTC are somewhat not capable to meet the demands for ubiquitous coverage of M2M communications. This ubiquitous access offered by satellite connections has prohibitive costs, posing major challenges when used in indoor environments. This therefore calls for the radio technologies which are capable of making available extensive coverage area with low power consumption and reduced cost. At the same time operation of such a new infrastructure network at a diverse scale makes it an economically challenging task, thus making it necessary to add the MTC devices in the services of the existing communication networks.
Figure 1.1 Cases for M2M connectivity. (a) Basic M2M connectivity, (b) M2M in which a single application shares information with of group of similar devices, and (c) M2M communication using the gateway device [8].
Figure 1.2 Applications of M2M communications [9].
Consumer attitude to usage of internet is altering due to the alteration in the tendencies. Such user demands can only be fulfilled by the widespread mobile network supporting the M2M communication offering higher efficiency, security and robustness. Current standards being designed to provide access to only a small count of devices are likely unable to cope with the expected growth in the traffic of the M2M communication networks, thereby becoming a major challenge for the 5G networks [8]. Due to this reason the major focus is to enforce the M2M services as shown in Figure 1.2, which involve myriad devices generating efficient periodic transmissions of short data, predicted to play a major role in the future networks.
This chapter surveys the major challenges presented to the wireless cellular network standards by the massive M2M services. Section 1.2 is the literature survey giving the current standards for enabling the M2M services. Section 1.3 addresses in greater detail the challenge of the same with their proposed solutions to fill the gaps in the future to fully support M2M. Section 1.4 concludes this chapter with the final reconsiderations.
1.2 Literature Survey
Researchers have predicted that more than a billion devices will connect with the M2M communications through mobile networks by 2020. Statistics show that the world cellular site visitors will experience increase around 70% with 26% smartphones accountable for 88% of whole cell facts visitors [9]. The current 4G mobile structures fail to aid this huge scale of information utilization when you consider that they had been in the beginning deliberate to keep up to 600 RCC related customers per cell [10, 11]. Relatively M2M communications and IoTs subsidize thousands of linked devices in a one cell. This makes the aforementioned essential to support the standards to enable the M2M communications.
The authors in [12] differentiated the M2M communications from mobile Human-based (H2H) because the H2H traffic (browsing, file transferring, video streaming) cannot be directly applied to the M2M [12, 13], mentioning the M2M traffic direction as uplink whereas the H2H traffic direction as downlink. The M2M applications duty-cycled with short connection would promise fast access to the M2M network, resolving major traffic problems in the M2M communications due to H2H traffic.
Due to increased H2H and M2M traffic, the Wi-Fi communications can't chorus from dealing with the new challenges of radio spectrum congestion. In [14], the authors surveyed to provide complete investigation of the M2M fading channels in coordinated and cooperative networks under the propagation conditions of the line-of-sight (LOS)...
