Cyber Physical Systems - Advances and Applications

The Internet of Things (IoT) has become one of the most widely used technologies in recent times. IoT devices can be enabled to collect, and exchange information in a highly efficient manner via the network. A smart object with technology and devices builds a network infrastructure that is used in a variety of areas such as mechanical, building, medical, manufacturing, entertainment, and transport. The major security issues such as confidentiality, authentication, confirmation, security systems, system configuration, data storage, and administration are the main challenges in an IoT environment. To overcome these security issues, various techniques are addressed. Initially software called an Intrusion Detection System (IDS) was used that monitors a network of malicious activity using valuable tools in IoT devices. Then, the machine technique was used to detect the attacks from the intrusion detection system to provide embedded intelligence in IoT devices and networks. Finally, Blockchain (BC) technology is gaining traction in modern IoT devices to address security and privacy challenges to provide reliable communication in an IoT environment. The aim of this work is to provide a detailed review of ML and BC techniques that can be used to develop revamped IoT security devices. 

A smart grid cyber physical system (SG-CPS) is an optimal fusion of a power network infrastructure and cyber system based on a communicating network. The SG-CPS employs advanced technologies to deliver energy supply and provide flexible choices for prosumers. The SG-CPS uses multiple components in different units and this has given rise to more complexity in managing them. The reliable operation of any smart grid is necessary to enjoy uninterrupted services. As many smart devices are being used, more cyber-attacks are also targeted on smart grid cyber physical systems. The different types of attacks necessitate a broad security perspective to ensure safe services in the smart grid. The countermeasures for securing the smart grid have to be designed in all layers encompassing the cyber physical power system. If the power system is targeted then all the dependent devices will be at risk. A blackout scenario will cause more damage to industrial and household applications. Emerging technologies like Blockchain, AI, ML and IoT present a promising trend in the smart grid cyber-physical system. By predicting the power demand, supply can be adjusted automatically. Many such power system-related issues have smart solutions. In this chapter, we will first review the security challenges and attacks in the context of smart grid cyber-physical systems. Then the potential vulnerabilities to cyber-attack threats and risks in smart grid cyber-physical systems have been outlined. Finally, countermeasures for the security attack scenarios in SG-CPS are outlined.

Cyber Physical Systems (CPS) is a new generation of systems with integrated control, communication, and computation capabilities in the modern world. Just as the Internet changed the way people interacted with one another, cyber physical systems will change how people engage with the real environment. Currently, CPS research is in its infancy, and numerous research concerns and obstacles exist in areas such as electricity, health care, transportation and smart construction, agriculture, and others. The architecture of CPS and Wireless Sensor Networks (WSNs) for cloud computing for life support or healthcare and its application for monitoring and decision support systems are introduced in this article. The suggested CPS architecture is made up of three primary components: 1) communication, 2) computing, and 3) resource management for healthcare. Industry, agriculture, and hospitals are all being transformed by this type of integration, known as Cyber-physical Systems. CPS enables the systematic transformation of large amounts of data into information, revealing previously unseen patterns of degradation and inefficiency and resulting in an optimal decision-making system. This article focuses on current trends in hospital big data analytics and CPS development. Relevant concepts such as cloud computing, realtime scheduling, and security models are thoroughly examined and explained. Finally, a healthcare application section is offered, which is based on our long-running practical test bed. Many businesses and hospitals are confronting new opportunities and problems as Information and Communication Technologies (ICT) improve and advanced analytics are integrated into manufacturing, goods, and services. Finally, a case study using the CPS to construct intelligent machines is provided. 

 In today’s world, the demand for autonomous and unmanned aerial vehicles is rapidly growing with applications in many domains. These autonomous vehicles have potential advantages like – a reduction in traffic deaths by 90%, a drop in harmful emissions by 60%, an improvement in fuel economy by 10%, an increase in lane capacity by 500%, a reduction in travel time by 40%, an increase in transportation accessibility and a reduction in transportation costs. Similarly, UAVs have advantages like- traffic monitoring, moving objects in seemingly dangerous environments, payload delivery and surveillance. Cyber-Physical Systems (CPS) are combinations of networking, computation and physical systems. The three interacting components of CPS - communication, computation, control and their coupling effects are necessary for improving the performance of the UAV network. Control mechanisms, performance and safety of autonomous and unmanned aerial vehicles are the important factors to be considered while designing them.The major concern for any fully or partially autonomous system is safety, the other challenges faced are: mechanical failure, communication bandwidth shortage, cyber-hacking, communication delay, etc. Various designs are proposed and tested to overcome these challenges, few of them are: a framework for software - ReMinds in addition to the extensions implemented in the Dronology system; for Dronology, researchers have proposed and designed incubators for safety-critical CPS. The chapter emphasizes the role of CPS in autonomous and unmanned aerial vehicles, framework of CPS for UAVs, the challenges with respect to CPS and is concluded with the state of art of the present autonomous vehicles.

A cyber-physical system is a computer system that operates or monitors a mechanism using computer-based algorithms. Due to the rapid evolution of CPS in today's world, a greater range of services and applications involving e-Health, smart homes, e-Commerce, and industry automation may be easily realized, affecting numerous parts of people's lives. Smart grid, autonomous underwater, and UAVs, gas and oil pipeline monitoring and control, smart factory and manufacturing, pollution control, and HEVs are among the most prominent applications in this domain.

However, interconnecting the cyber and physical worlds introduces new security threats. Security attacks can result in trouble to essential infrastructure and business continuity, including production-performance deterioration, severe commercial risks, unavailability of critical services, and regulatory violations. Cybersecurity attacks are one of the most serious dangers to CPS due to the system's complexity and interdependencies, owing to which risk management is difficult considering recent attack trends. The first section of the manuscript discusses the evolution of CPS and its wide range of applications in different areas, followed by in-depth insights into the industrial sector. Types of cyber and physical threats, as well as examples, various system components, related algorithms and models, attack characteristics, and defense measures, are explained. Current study classifications are assessed and summarized using various system modeling and analytic approaches along with the benefits and drawbacks of various techniques. The chapter is concluded by stating future research topics on secure CPS and potential solutions. 4 Cyber-physical systems -Advances and Applications Rajendran et al. 

Cyber-Physical Systems (CPS) are being developed with the integration of computational capabilities and communication with physical systems. Recent technologies like WSN (Wireless Sensor Networks), Communication Networks, Cloud Computing, Big Data, and many more use CPS. Applications include Smart Grid, Healthcare, Transportation, and Smart Buildings. CPS has made a huge impact on increasing the efficiency of medicines and life span in many developed countries. This has drawn researchers and the government's interest in Medical Cyber-Physical Systems (MCPS), especially during Covid times. Many models were developed during the pandemic. One of them is a Machine Learning (ML) integrated X-ray device called Covilearn. In this chapter, an introduction to CPS in health care, its current trends, and a device called e-stocking has been discussed. It is being used to treat leg venous insufficiency. The motive of the application of CPS is to reduce power consumption for long-term usage. This system is based on a model-driven energy-aware approach. There are three approaches - Mechanical, Software, and Communication. False alarm is one of the major issues as it is a pressure on both patients and caretakers. A model aimed at resolving this problem is proposed and discussed here. Also, the existing challenges and prospective opportunities in the domain of CPS have been explored.

With the increase in high volume, velocity, and variety of data, the traditional data analysis approaches are not adequate to handle diverse analysis challenges. Traditionally, a data warehouse is being used which is an integrated repository from various sources used for management and decision-making in business. Data is already in a transformed and structured format stored in a costly but reliable storage device. The data warehouse does not include all the data that may be not required at the time of construction of the data warehouse. With the advent of big data and to handle the data silos problem, the concept of Data Lake is introduced to handle data analysis. Data lakes have not replaced the data warehouse but rather complement it. In this chapter, firstly Data Lake is introduced and compared with predecessor technologies, then various tools and techniques are discussed to implement Data Lake.

 It is self-evident that recently, humanity has entered the fourth industrial revolution. With the advent of the Internet of Things, cloud computing, and Artificial Intelligence, industrial critical infrastructures such as power plants, oil and gas plants, heavy industries, nuclear plants, and water treatment facilities are experiencing disruptive growth. This era of industrialization, nevertheless, has carried with it its new myriad of issues, notably regarding cyber security threats. Nowadays, industrial processes are openly connected to the internet, and internet-connected machines are almost always highly susceptible to security breaches by adversaries despite sufficient cyber security safeguards. Intrusion detection systems (IDS) are designed to employ classification models to detect malicious attacks such as service attacks, probing attacks, etc. In intrusion detection, the phase that reduces the number of similar traffic attributes while sustaining the accuracy of classification is a requirement that considerably improves an intrusion detection system's overall efficacy. This chapter focuses on (i) various feature selection methods in IDS, (ii) ML&DL classification models in IDS of industrial systems, (iii) Various ensemble feature selection models are analyzed, and a novel ensemble feature selection model for IDS is proposed.