Cyber-Physical Systems E-Book
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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
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 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.
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Veröffentlichungsjahr: 2022
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Table of Contents
Cover
Title Page
Copyright
Preface
Acknowledgement
1 A Systematic Literature Review on Cyber Security Threats of Industrial Internet of Things
1.1 Introduction
1.2 Background of Industrial Internet of Things
1.3 Literature Review
1.4 The Proposed Methodology
1.5 Experimental Requirements
1.6 Conclusion
References
2 Integration of Big Data Analytics Into Cyber-Physical Systems
2.1 Introduction
2.2 Big Data Model for Cyber-Physical System
2.3 Big Data and Cyber-Physical System Integration
2.4 Storage and Communication of Big Data for Cyber-Physical System
2.5 Big Data Processing in Cyber-Physical System
2.6 Applications of Big Data for Cyber-Physical System
2.7 Security and Privacy
2.8 Conclusion
References
3 Machine Learning: A Key Towards Smart Cyber-Physical Systems
3.1 Introduction
3.2 Different Machine Learning Algorithms
3.3 ML Use-Case in MATLAB
3.4 ML Use-Case in Python
3.5 Conclusion
References
4 Precise Risk Assessment and Management
4.1 Introduction
4.2 Need for Security
4.3 Different Kinds of Attacks
4.4 Literature Survey
4.5 Proposed Work
4.6 Conclusion
References
5 A Detailed Review on Security Issues in Layered Architectures and Distributed Denial Service of Attacks Over IoT Environment
5.1 Introduction
5.2 IoT Components, Layered Architectures, Security Threats
5.3 Taxonomy of DDoS Attacks and Its Working Mechanism in IoT
5.4 Existing Solution Mechanisms Against DDoS Over IoT
5.5 Challenges and Research Directions
5.6 Conclusion
References
6 Machine Learning and Deep Learning Techniques for Phishing Threats and Challenges
6.1 Introduction
6.2 Phishing Threats
6.3 Deep Learning Architectures
6.4 Related Work
6.5 Analysis Report
6.6 Current Challenges
6.7 Conclusions
References
7 Novel Defending and Prevention Technique for Man-in-the-Middle Attacks in Cyber-Physical Networks
7.1 Introduction
7.2 Literature Review
7.3 Classification of Attacks
7.4 Proposed Algorithm of Detection and Prevention
7.5 Results and Discussion
7.6 Conclusion and Future Scope
References
8 Fourth Order Interleaved Boost Converter With PID, Type II and Type III Controllers for Smart Grid Applications
8.1 Introduction
8.2 Modeling of Fourth Order Interleaved Boost Converter
8.3 Controller Design for FIBC
8.4 Computational Results
8.5 Conclusion
References
9 Industry 4.0 in Healthcare IoT for Inventory and Supply Chain Management
9.1 Introduction
9.2 Benefits and Barriers in Implementation of RFID
9.3 IoT-Based Inventory Management—Case Studies
9.4 Proposed Model for RFID-Based Hospital Management
9.5 Conclusion and Future Scope
References
10 A Systematic Study of Security of Industrial IoT
10.1 Introduction
10.2 Overview of Industrial Internet of Things (Smart Manufacturing)
10.3 Industrial Reference Architecture
10.4 FIWARE Generic Enabler (FIWARE GE)
10.5 Discussion
10.6 Conclusion
References
11 Investigation of Holistic Approaches for Privacy Aware Design of Cyber-Physical Systems
11.1 Introduction
11.2 Popular Privacy Design Recommendations
11.3 Current Privacy Challenges in CPS
11.4 Privacy Aware Design for CPS
11.5 Limitations
11.6 Converting Risks of Applying AI Into Advantages
11.7 Conclusion and Future Scope
References
12 Exposing Security and Privacy Issues on Cyber-Physical Systems
12.1 Introduction to Cyber-Physical Systems (CPS)
12.2 Cyber-Attacks and Security in CPS
12.3 Privacy in CPS
12.4 Conclusion & Future Trends in CPS Security
References
13 Applications of Cyber-Physical Systems
13.1 Introduction
13.2 Applications of Cyber-Physical Systems
13.3 Conclusion
References
Index
End User License Agreement
List of Illustrations
Chapter 1
Figure 1.1 Challenges in artificial intelligence-based IIoT security model.
Figure 1.2 The industrial revolutions.
Figure 1.3 Deep incremental learning-based IIoT security model.
Chapter 3
Figure 3.1 (a) Structure of basic artificial neuron, (b) sigmoidal activation fu...
Figure 3.2 (a) SVM Classifier and (b) structure of confusion matrix.
Figure 3.3 Classification learner app in Matlab.
Chapter 4
Figure 4.1 Cyber threats area-wise.
Figure 4.2 Malware infections year-wise.
Figure 4.3 Simulated results.
Chapter 5
Figure 5.1 Applications of IoT.
Figure 5.2 Growth of IoT devices in billions.
Figure 5.3 DDoS capable IoT malware growth.
Figure 5.4 IoT components.
Figure 5.5 3-Layer architecture.
Figure 5.6 4-Layer architecture.
Figure 5.7 5-Layer architecture.
Figure 5.8 Phases of DDoS attack.
Figure 5.9 (a) Agent-Handler Model; (b) Reflector Model; (c) IRC based model; (d...
Figure 5.10 Working mechanism of DDoS attacks.
Chapter 6
Figure 6.1 Phishing fraud [22]. (a) Gender wise phishing victims. (b) Age wise p...
Figure 6.2 Analysis report on phishing fraud. (a) Total no. of phishing articles...
Chapter 7
Figure 7.1 Different layers in a cyber-physical network.
Figure 7.2 Attacker creating a rogue access point with the same SSID and forcing...
Figure 7.3 Diagram showing a typical network with two different devices connecte...
Figure 7.4 Diagram showing attacker spoofing the access point as the victim and ...
Figure 7.5 A spoofed network with attacker as man in the middle hijacking every ...
Figure 7.6 A typical DNS server with records stored to resolve domain names to t...
Figure 7.7 Diagram showing how every request made by any user is first redirecte...
Figure 7.8 DNS server responding with a redirection request to the user for the ...
Figure 7.9 Attacker using DNS spoofing to redirect any request by the user to it...
Figure 7.10 mDNS spoofing attack by capturing every broadcast request and spoofi...
Figure 7.11 ARP table of a typical network with 192.168.0.1 as the gateway and o...
Figure 7.12 ARP table of a spoofed network with two different IP 192.168.0.1 and...
Figure 7.13 The ARP detection script explained using a detailed algorithm with a...
Figure 7.14 A test web page was developed, when the attacker tries to become man...
Figure 7.15 Script asking the user if he/she wants to disconnect from the networ...
Figure 7.16 User disconnected from the attacked network on choosing to disconnec...
Figure 7.17 No action taken even under ARP attack as the user decided to continu...
Figure 7.18 Algorithm for creation of SSL Certificates and its validation to pre...
Figure 7.19 A spoofed login page of Facebook.com but the domain contains three o...
Figure 7.20 Steps implemented in detection of DNS spoofing script and testing th...
Chapter 8
Figure 8.1 General configuration of fourth order interleaved boost converter.
Figure 8.2 General configuration of fourth order boost converter.
Figure 8.3 Mode 1 operation of FIBC.
Figure 8.4 Mode 2 operation of FIBC.
Figure 8.5 Mode 3 operation of FIBC.
Figure 8.6 Mode 4 operation of FIBC.
Figure 8.7 Root locus of G
vd
.
Figure 8.8 Root locus of G
vg
.
Figure 8.9 Comparison of Bode plots of the two transfer function of FIBC.
Figure 8.10 Response of FIBC with Type II controller.
Figure 8.11 Bode diagram of FIBC with Type II controller.
Figure 8.12 Root locus of FIBC with Type II controller.
Figure 8.13 Response of FIBC with PID controller.
Figure 8.14 FIBC with Type III controller.
Figure 8.15 FIBC with Type III controller-magnitude and phase plot.
Figure 8.16 Root locus of FIBC with Type III controller.
Figure 8.17 Comparison of the different controllers in closed loop operation.
Figure 8.18 Comparison of the bode response of different controllers in closed l...
Figure 8.19 Comparison of the three different controllers when 50% of reference ...
Figure 8.20 Comparison of the three different controllers when 50% of reference ...
Figure 8.21 Comparison of the changes in 10% of input voltage for different cont...
Figure 8.22 Comparison of the load regulation by adding additional load voltage ...
Figure 8.23 Ripple in the output of FIBC.
Chapter 9
Figure 9.1 Basic components of RFID based system.
Figure 9.2 IoT and RFID for hospital inventory control.
Figure 9.3 Working principle of RFID enabled tracking.
Figure 9.4 Automation of drug-supply.
Figure 9.5 Automated employee attendance.
Figure 9.6 Automation of SCM in Healthcare 4.0.
Figure 9.7 Working of automated theft detection system.
Figure 9.8 Tracking patients using RFIDs.
Figure 9.9 Automated complete solution to manage hospital.
Figure 9.10 Architecture of proposed model.
Figure 9.11 Working principle of proposed model.
Figure 9.12 Automation of inventory and pharmacy management.
Figure 9.13 Tracking of Patients and Localization using RFIDs.
Figure 9.14 Tracking of all entities in the hospital.
Figure 9.15 Modules in proposed system.
Chapter 10
Figure 10.1 Components model showing a unified perspective of IoT and CPS.
Figure 10.2 The traditional automation hierarchy of ISA-95.
Figure 10.3 OPC UA stack overview.
Figure 10.4 OPC UA information modeling framework.
Figure 10.5 The FIWARE principle components.
Figure 10.6 NGSIv2 data model conceptual diagram.
Figure 10.7 UML representation of NGSI-LD information model.
Figure 10.8 FIWARE IoT stack (Inspired by FIWARE Tour Guide).
Figure 10.9 Device to NGSI mapping interactions.
Figure 10.10 MQTT binding interactions of IoT Agent-JSON.
Figure 10.11 Request forwarding diagram of context provider.
Figure 10.12 A reference architecture for smart industry powered by FIWARE.
Chapter 12
Figure 12.1 Essential elements of CPS.
Figure 12.2 Cyber-attacks of CPS.
Figure 12.3 Future scope for CPS.
Chapter 13
Figure 13.1 Building blocks of cyber-physical systems.
List of Tables
Chapter 1
Table 1-1 Comparison charts.
Chapter 3
Table 3.1 Sample data set for power system fault classification.
Table 3.2 Code for data normalization in Matlab.
Table 3.3 A sample regression implementation through Matlab m-file.
Table 3.4 A sample Classification implementation through Matlab m-file.
Table 3.5 Calling the libraries in python.
Table 3.6 Logistic regression and K nearest neighbor algorithm in python.
Table 3.7 Regression algorithm in python.
Chapter 4
Table 4.1 Notations used in the contribution.
Table 4.2 Representation of sources and its priorities.
Table 4.3 Simulation parameters.
Chapter 5
Table 5.1 Attacks in every layer of IoT architecture.
Table 5.2 Summary of existing countermeasures against DDoS attacks.
Table 5.3 DDoS capable malwares.
Chapter 6
Table 6.1 Categories of electronic mail frauds.
Table 6.2 Categories of phishing extortion.
Table 6.3 Categories of extortion fraud.
Table 6.4 Categories of social media scam.
Table 6.5 Categories of tourism fraud.
Table 6.6 Categories of excise fraud.
Table 6.7 Deep learning architectures.
Table 6.8 CNN models.
Table 6.9 RNN variants.
Table 6.10 LSTM variants.
Table 6.11 Machine Learning approach.
Table 6.12 Neural network approach.
Table 6.13 Deep learning approach.
Chapter 8
Table 8.1 Converter parameters.
Table 8.2 Comparison of different controllers in closed loop performance.
Chapter 9
Table 9.1 Success results of implementing IoT inventory system at BJC healthcare...
Guide
Cover
Table of Contents
Title Page
Copyright
Preface
Acknowledgement
Begin Reading
Index
End User License Agreement
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Scrivener Publishing
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Beverly, MA 01915-6106
Publishers at Scrivener
Martin Scrivener ([email protected])
Phillip Carmical ([email protected])
Cyber-Physical Systems
Foundations and Techniques
Edited by
Uzzal Sharma
Parma Nand
Jyotir Moy Chatterjee
Vishal Jain
Noor Zaman Jhanjhi
and
R. Sujatha
This edition first published 2022 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA
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Preface
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 System”. 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 of the exciting innovations such as autonomous cars, quadcopter, space ships, sophisticated medical devices fall under CPS. The scope of CPS is tremendous. In CPS, we can see the applications of various emerging technologies such as artificial intelligence, Internet of Things (IoT), machine learning (ML), deep learning (DL), big data (BD), robotics, quantum technology, etc. Almost in all the sectors whether it is education, health, human resource development, skill improvement, startup strategy, etc., we see an enhancement in the quality output, which is because of the emergence of CPS into the field. The CPS is considered the upcoming industry revolution.
This book is covering the different aspects associated with the CPS, such as algorithms, application areas, improvement of existing technology to name a few. The book has 13 quality chapters written by experts in their field. The details of each chapter are as follows:
Chapter 1 presents a systematic literature review on cyber security threats of the industrial Internet of Things (IIoT). In recent years, the IIoT has become one of the popular technologies among Internet users for transportation, business, education, and communication development.
Chapter 2 explains the integration of big data analytics into CPS. The evolving CPS technology advances BD analytics and processing. The control and management of BD are aided by the architecture of CPS with cyber layer, physical layer, and communication layer is designed which not only integrates but also helps CPS in decision-making.
Chapter 3 deals with the basics of machine learning techniques. Embedding these techniques in a CPS can make the system intelligent and user-friendly. ML aims to develop computer programs, that not only process the data to generate output, but also gain information from that data simultaneously, to improve its performance in every next run.
Chapter 4 presents a precise risk assessment and management strategy.
Chapter 5 presents a detailed review on security issues in layered architectures and distributed denial service of attacks over the IoT environment: As a part of evolution, the current trend is the IoT, which brings automation to the next level via connecting the devices through the Internet, and its benefits are tremendous. Meanwhile, the threats and attacks are also evolving and become an unstoppable menace to IoT users and applications. This chapter addresses critical challenges and future research directions concerning IoT security that gives insights to the new researchers in this domain.
Chapter 6 presents ML and DL (deep learning) techniques for phishing threats and challenges: Internet security threats keep on rising due to the vulnerabilities and numerous attacking techniques. The swindlers who take skills over the vulnerable online services and get admission to the information of genuine people through these virtual features continue to expand. Security should prevent phishing attacks and to offer availability and confidentiality. The phishing attack using AI is discussed in this chapter.
Chapter 7 presents a novel defending and prevention technique for the man in the middle of attacks in cyber-physical networks: Man in the Middle Attack is a type of cyber-attack in which an unauthorized person enters the online network between the two users, avoiding the sight of both users. The scripts developed successfully defended the deployed virtual machines from the Man in the Middle Attacks. The main purpose behind this topic is to make readers beware of cyber-attacks.
Chapter 8 presents the fourth-order interleaved Boost Converter with PID, Type II and Type III controller for smart grid applications: Switched-mode power converters are an important component in interfacing renewable energy sources to smart grids and microgrids. The voltage obtained from power conversion is usually full of ripples. To minimize the ripple in the output, certain topological developments are made. This is made possible by controlling the converters using Type II and Type III controllers and the results are compared with PID controller. The performance is analyzed and compared in the Simulink environment. The transient and steady-state analysis is done for a better understanding of the system.
Chapter 9 presents Industry 4.0 in HealthCare IoT for inventory and supply chain management. Industry 4.0 is a setup reality that fulfills various necessities of the clinical field with expansive assessment. Radio Frequency Identification (RFID) advancement does not simply offer the capacity to discover stuff, supplies, and people persistently, but it also gives capable and exact permission to clinical data for prosperity specialists.
Chapter 10 presents a systematic literature review on the security aspects of the Industrial IoT.
Chapter 11 acts as a readymade guide to researchers who want to know how to lay foundations towards a privacy-aware CPS architecture.
Chapter 12 explains the possible privacy and security issues of CPS.
Chapter 13 presents a review of the various application of the CPS.
Uzzal Sharma, Assam, IndiaParma Nand, Greater Noida, IndiaJyotir Moy Chatterjee, Kathmandu, NepalVishal Jain, Greater Noida, IndiaNoor Zaman Jhanjhi, Subang Jaya, MalaysiaR. Sujatha, Vellore, IndiaApril 2022
Acknowledgement
I would like to acknowledge the most important people in my life, i.e., my grandfather Late Shri. Gopal Chatterjee, grandmother Late Smt. Subhankori Chatterjee, my father Shri. Aloke Moy Chatterjee, my Late mother Ms. Nomita Chatterjee & my uncle Shri Moni Moy Chatterjee. The is book has been my long-cherished dream which would not have been turned into reality without the support and love of these amazing people. They have continuously encouraged me despite my failure to give them the proper time and attention. I am also grateful to my friends, who have encouraged and blessed this work with their unconditional love and patient.
Jyotir Moy ChatterjeeDepartment of ITLord Buddha Education Foundation(Asia Pacific University of Technology & Innovation)Kathmandu, Nepal-44600
2Integration of Big Data Analytics Into Cyber-Physical Systems
Nandhini R.S.*and Ramanathan L.
Computer Science and Engineering, Vellore Institute of Technology, Vellore, India
Abstract
The evolving Cyber-Physical Systems technology advances the big data analytics and processing. The chapter discusses the topics of Big Data which are required for Cyber-Physical Systems across all data streams including the heterogeneous data resource integration. The challenges such as integration of data generated from multiple sources into cyber-physical systems, big data for conventional databases and offline processing, scalability are further considered. The control and management of big data is aided by the architecture of cyber-physical system with cyber layer, physical layer and communication layer is designed which not only integrates but also helps cyber-physical system in decision making. The case study that aids big data processing and analytics in cyber-physical system is stated.
Keywords: Cyber-Physical systems, big data analytics and processing, Internet of Things, data mining
2.1 Introduction
The rapid growth in things or devices in particular sensors and actuators made the development to control the smart physical things, smart objects and digital technologies such as machines in smart manufacturing and structures in smart cities, etc. possible. The communication technologies and physical devices are merged to generate systems that are effective, productive, safe called intelligent systems, where the integrations and interactions are combined to create a global cyber-physical system. A cyber-physical system is the association of cyber and physical components that have been specifically engineered to monitor, coordinate and control based on computational algorithms. It is a 3C technology—communication, computation, and control. Cyber-physical systems capture the data from the wireless sensor devices and monitor them, the control of the physical devices is based on the physical data using actuators, thus interacting both with the physical and cyber world in the real environment. These systems are interconnected with each other on a universal scale using different network and communication resources. The physical control is efficient when the data collected from the sensors are processed for information with data mining techniques. The interaction among the users from context perspective, the physical device’s surroundings and the process in the cyber-physical systems are observed when the features of cyber-physical system are considered. However, the integration rules, interoperation among the devices, control of cyber-physical system are the functions that are globally distributed and networked in real-time [1]. This system is used extensively in many applications such as industries, transport and vehicular industry, medical and health management, smart grids, military applications, weather forecasting and many more.
