CYBER-PHYSICAL SYSTEMS The 13 chapters in this book cover the various aspects associated with Cyber-Physical Systems (CPS) such as algorithms, application areas, and the improvement of existing technology such as machine learning, big data and robotics. Cyber-Physical Systems (CPS) is the interconnection of the virtual or cyber and the physical system. It is realized by combining three well-known technologies, namely "Embedded Systems," "Sensors and Actuators," and "Network and Communication Systems." These technologies combine to form a system known as CPS. In CPS, the physical process…mehr
The 13 chapters in this book cover the various aspects associated with Cyber-Physical Systems (CPS) such as algorithms, application areas, and the improvement of existing technology such as machine learning, big data and robotics.
Cyber-Physical Systems (CPS) is the interconnection of the virtual or cyber and the physical system. It is realized by combining three well-known technologies, namely "Embedded Systems," "Sensors and Actuators," and "Network and Communication Systems." These technologies combine to form a system known as CPS. In CPS, the physical process and information processing are so tightly connected that it is hard to distinguish the individual contribution of each process from the output. Some exciting innovations such as autonomous cars, quadcopter, spaceships, sophisticated medical devices fall under CPS.
The scope of CPS is tremendous. In CPS, one sees the applications of various emerging technologies such as artificial intelligence (AI), Internet of Things (IoT), machine learning (ML), deep learning (DL), big data (BD), robotics, quantum technology, etc. In almost all sectors, whether it is education, health, human resource development, skill improvement, startup strategy, etc., one sees an enhancement in the quality of output because of the emergence of CPS into the field.
Audience Researchers in Information technology, artificial intelligence, robotics, electronics and electrical engineering.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Uzzal Sharma, PhD, is an assistant professor (senior), Department of Computer Applications, School of Technology, Assam Don Bosco University, Guwahati, India. Parma Nand, PhD, in Computer Science & Engineering from Indian Institute of Technology, Roorkee, and has more than 27 years of experience, both in industry and academia. Jyotir Moy Chatterjee is an assistant professor in the Information Technology department at Lord Buddha Education Foundation (LBEF), Kathmandu, Nepal. Vishal Jain, PhD, is an associate professor in the Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University, Greater Noida, U. P. India. Noor Zaman Jhanjhi, PhD, is an associate professor, Director of the Center for Smart Society 5.0 at the School of Computer Science and Engineering, Faculty of Innovation and Technology, Taylor's University, Malaysia. R. Sujatha, PhD, is an associate professor in the School of Information Technology and Engineering in Vellore Institute of Technology, Vellore, India.
Inhaltsangabe
Preface xv
Acknowledgement xix
1 A Systematic Literature Review on Cyber Security Threats of Industrial Internet of Things 1 Ravi Gedam and Surendra Rahamatkar
1.1 Introduction 2
1.2 Background of Industrial Internet of Things 3
1.3 Literature Review 6
1.4 The Proposed Methodology 13
1.5 Experimental Requirements 14
1.6 Conclusion 15
References 16
2 Integration of Big Data Analytics Into Cyber-Physical Systems 19 Nandhini R.S. and Ramanathan L.
2.1 Introduction 19
2.2 Big Data Model for Cyber-Physical System 21
2.2.1 Cyber-Physical System Architecture 22
2.2.2 Big Data Analytics Model 22
2.3 Big Data and Cyber-Physical System Integration 23
2.3.1 Big Data Analytics and Cyber-Physical System 23
2.3.1.1 Integration of CPS With BDA 24
2.3.1.2 Control and Management of Cyber-Physical System With Big Data Analytics 24
2.3.2 Issues and Challenges for Big Data-Enabled Cyber-Physical System 25
2.4 Storage and Communication of Big Data for Cyber-Physical System 26
2.4.1 Big Data Storage for Cyber-Physical System 27
2.4.2 Big Data Communication for Cyber-Physical System 28
2.5 Big Data Processing in Cyber-Physical System 29
2.5.1 Data Processing 29
2.5.1.1 Data Processing in the Cloud and Multi-Cloud Computing 29
2.5.1.2 Clustering in Big Data 31
2.5.1.3 Clustering in Cyber-Physical System 32
2.5.2 Big Data Analytics 32
2.6 Applications of Big Data for Cyber-Physical System 33
2.6.1 Manufacturing 33
2.6.2 Smart Grids and Smart Cities 34
2.6.3 Healthcare 35
2.6.4 Smart Transportation 35
2.7 Security and Privacy 36
2.8 Conclusion 37
References 38
3 Machine Learning: A Key Towards Smart Cyber-Physical Systems 43 Rashmi Kapoor, Chandragiri Radhacharan and Sung-ho Hur
3.1 Introduction 44
3.2 Different Machine Learning Algorithms 46
3.2.1 Performance Measures for Machine Learning Algorithms 48
3.2.2 Steps to Implement ML Algorithms 49
3.2.3 Various Platforms Available for Implementation 50
3.2.4 Applications of Machine Learning in Electrical Engineering 50
3.3 ML Use-Case in MATLAB 51
3.4 ML Use-Case in Python 56
3.4.1 ML Model Deployment 59
3.5 Conclusion 60
References 60
4 Precise Risk Assessment and Management 63 Ambika N.
4.1 Introduction 64
4.2 Need for Security 65
4.2.1 Confidentiality 65
4.2.2 Integrity 66
4.2.3 Availability 66
4.2.4 Accountability 66
4.2.5 Auditing 67
4.3 Different Kinds of Attacks 67
4.3.1 Malware 67
4.3.2 Man-in-the Middle Assault 69
4.3.3 Brute Force Assault 69
4.3.4 Distributed Denial of Service 69
4.4 Literature Survey 70
4.5 Proposed Work 75
4.5.1 Objective 75
4.5.2 Notations Used in the Contribution 76
4.5.3 Methodology 76
4.5.4 Simulation and Analysis 78
4.6 Conclusion 80
References 80
5 A Detailed Review on Security Issues in Layered Architectures and Distributed Denial Service of Attacks Over IoT Environment 85 Rajarajan Ganesarathinam, Muthukumaran Singaravelu and K.N. Padma Pooja
1 A Systematic Literature Review on Cyber Security Threats of Industrial Internet of Things 1 Ravi Gedam and Surendra Rahamatkar
1.1 Introduction 2
1.2 Background of Industrial Internet of Things 3
1.3 Literature Review 6
1.4 The Proposed Methodology 13
1.5 Experimental Requirements 14
1.6 Conclusion 15
References 16
2 Integration of Big Data Analytics Into Cyber-Physical Systems 19 Nandhini R.S. and Ramanathan L.
2.1 Introduction 19
2.2 Big Data Model for Cyber-Physical System 21
2.2.1 Cyber-Physical System Architecture 22
2.2.2 Big Data Analytics Model 22
2.3 Big Data and Cyber-Physical System Integration 23
2.3.1 Big Data Analytics and Cyber-Physical System 23
2.3.1.1 Integration of CPS With BDA 24
2.3.1.2 Control and Management of Cyber-Physical System With Big Data Analytics 24
2.3.2 Issues and Challenges for Big Data-Enabled Cyber-Physical System 25
2.4 Storage and Communication of Big Data for Cyber-Physical System 26
2.4.1 Big Data Storage for Cyber-Physical System 27
2.4.2 Big Data Communication for Cyber-Physical System 28
2.5 Big Data Processing in Cyber-Physical System 29
2.5.1 Data Processing 29
2.5.1.1 Data Processing in the Cloud and Multi-Cloud Computing 29
2.5.1.2 Clustering in Big Data 31
2.5.1.3 Clustering in Cyber-Physical System 32
2.5.2 Big Data Analytics 32
2.6 Applications of Big Data for Cyber-Physical System 33
2.6.1 Manufacturing 33
2.6.2 Smart Grids and Smart Cities 34
2.6.3 Healthcare 35
2.6.4 Smart Transportation 35
2.7 Security and Privacy 36
2.8 Conclusion 37
References 38
3 Machine Learning: A Key Towards Smart Cyber-Physical Systems 43 Rashmi Kapoor, Chandragiri Radhacharan and Sung-ho Hur
3.1 Introduction 44
3.2 Different Machine Learning Algorithms 46
3.2.1 Performance Measures for Machine Learning Algorithms 48
3.2.2 Steps to Implement ML Algorithms 49
3.2.3 Various Platforms Available for Implementation 50
3.2.4 Applications of Machine Learning in Electrical Engineering 50
3.3 ML Use-Case in MATLAB 51
3.4 ML Use-Case in Python 56
3.4.1 ML Model Deployment 59
3.5 Conclusion 60
References 60
4 Precise Risk Assessment and Management 63 Ambika N.
4.1 Introduction 64
4.2 Need for Security 65
4.2.1 Confidentiality 65
4.2.2 Integrity 66
4.2.3 Availability 66
4.2.4 Accountability 66
4.2.5 Auditing 67
4.3 Different Kinds of Attacks 67
4.3.1 Malware 67
4.3.2 Man-in-the Middle Assault 69
4.3.3 Brute Force Assault 69
4.3.4 Distributed Denial of Service 69
4.4 Literature Survey 70
4.5 Proposed Work 75
4.5.1 Objective 75
4.5.2 Notations Used in the Contribution 76
4.5.3 Methodology 76
4.5.4 Simulation and Analysis 78
4.6 Conclusion 80
References 80
5 A Detailed Review on Security Issues in Layered Architectures and Distributed Denial Service of Attacks Over IoT Environment 85 Rajarajan Ganesarathinam, Muthukumaran Singaravelu and K.N. Padma Pooja
