Artificial Intelligence Application in Cybersecurity and Cyberdefense

Recently, extensive research into healthcare services and their technological advancements is being carried out globally. The Internet of Things (IoT) has proven to be a predominantly potential candidate in these advancements. IoT supports infrastructure development in connecting a wide range of medical devices, sensors, and health practitioners in order to ensure the best medical treatment for patients in both cities and remote places. This has enabled the IoT to provide major support in medical application, giving rise to assisted healthcare facilities. The IoT ecosystem has a complicated architecture, with several components interacting and an evolving variety of applications for users. This is a comprehensive and interdependent system that involves real-time data analysis, interconnections of device, data transfers, and analysis. The IoT creates a connected ecosystem developed from several intelligent systems that integrates respondents with machines and allows for statistics decision making. A network of interconnected devices that perceive vital data related to medical conditions of patients in real time is referred to as the Internet of Medical Things (IoMT), a healthcare application of IoT technology. Sensors used for sensing real-time data related to monitoring temperature, blood pressure levels, heartbeat levels, specialized signal converters, and communication interfaces can be added to existing medical facilities to turn them into IoMT devices. IoMT can be used to create wearable devices, home-care and personal-care medical devices, and mobile healthcare apps, along with creating communication with medical specialists in a given area. The IoMT system’s challenges and ecosystem interface requirements are also a matter of concern considering the complexity of the systems. This study offers a comprehensive evaluation of the various domains of use of IoMT, as well as its future scope and challenges. Recent advances in sensor technology, networks, cloud storage and processing, mobility, and big data analytics have made it possible to create affordable smart medical devices and a connected healthcare environment.

The Internet of Things (IoT) gives a strong structure for connecting things to the internet to facilitate Machine to Machine (M2M) communication and data transmission through basic network protocols such as TCP/IP. IoT is growing at a fast pace, and billions of devices are now associated, with the amount expected to reach trillions in the coming years. Many fields, including the army, farming, manufacturing, healthcare, robotics, and biotechnology, are adopting IoT for advanced solutions as technology advances. This paper offers a detailed view of the current IoT paradigm, specifically proposed for robots, namely the Internet of Robotic Things (IoRT). IoRT is a collection of various developments such as Cloud Computing, Artificial Intelligence (AI), Machine Learning, and the (IoT). This paper also goes over architecture, which would be essential in the design of Multi-Role Robotic Systems for IoRT. Furthermore, includes systems underlying IoRT, as well as IoRT implementations. The paper provides the foundation for researchers to imagine the idea of IoRT and to look beyond the frame while designing and implementing IoRT-based robotic systems in real-world implementations.

Today’s networked society is populated by complex business ecosystems that have moved away from the centralised firm-centric structure to a more distributed, crowd-driven ecosystem structure that adopts an open participatory value creation model. Such crowd-driven ecosystems take advantage of technological advancements and underlying network effects in order to harness the collective power and intelligence of the crowd. This ability to co-create value by actively collaborating with the crowd has been fueled by the Internet of Things (IoT) introducing new user-centric paradigms, such as mobile crowd sensing (MCS), which leverage the power and the wisdom of the crowd to observe, measure, and make sense of particular phenomena by exploiting user-owned mobile and wearable devices. Crowd-driven IoT ecosystems have emerged taking advantage of technological advancements and underlying network effects in order to harness the collective power and intelligence of the crowd. However, although research in the context of business ecosystems and business models has gained substantial importance in recent years, there is still a limited understanding of the business dynamics of these emerging, technologically advanced, crowddriven ecosystems. The vast majority of existingresearch efforts place emphasis on business models in the IoT context and only a few studies consider business models for IoT ecosystems. However, one can identify a research gap in relation to business models for crowd-driven ecosystems in the IoT context. This study aims to contribute to the emerging crowd-driven IoT ecosystems literature by examining business models in such environments. For this reason both an exploratory and explanatory research approach is employed. This study provides an exploratory review analysis that synthesizes current scientific knowledge and an explanatory framework that facilitates the analysis of business model components and frameworks that correspond to the needs of firm-centric and ecosystem-centric IoT environments. The study concludes by providing suggestions for the business model development for technologically advanced, crowd-driven ecosystems as in the area of IoT based on its findings, establishing this way a solid foundation for future research in the area of crowd-driven IoT ecosystems.

Smart farming with accurate greenhouses needs to be implemented for better farming growth management, and therefore, precision agriculture monitoring in diverse conditions is required. The Internet of Things (IoT) is a new era in computer communication that is gaining traction due to its vast range of applications in project development. The IoT provides individuals with smart and remote approaches, such as smart agriculture, smart environment, smart security, and smart cities. This is the most recent technology that is making things easier these days. The Internet of Things (IoT) has fundamentally expanded remote distance control and the diversity of networked things or devices, which is an intriguing element. The IoT comprises the hardware as well as the Internet connectivity to the real-time application. Sensors, actuators, embedded systems, and an Internet connection are the key components of the Internet of Things. As a result, we are interested in creating a smart farm IoT application. In greenhouse agriculture, this study presented a remote sensing of parameters and control system. The objective is to manage CO2, temperature, soil moisture, humidity, and light, with regulating actions for greenhouse windows/doors dependent on crops being carried out once a quarter throughout the year. The major goal is to properly regulate greenhouse conditions in accordance with plant requirements, in order to enhance output and provide organic farming. The results show that the greenhouse may be controlled remotely for CO2, temperature, soil moisture, humidity, and light, resulting in improved management.

Artificial intelligence (AI) is the ability of any mechanical device to imitate human intelligence processes. Machine learning (ML) is a technology subset of AI that searches through data, understands them, predicts the pattern, and independently builds an algorithm, thus allowing the computers to become independent and program automatically. The “Internet of things (IoT)” is a revolutionary technology that embeds the Internet into physical devices, thus granting them capabilities of identification and utilization of whatever form of input/output they are designed to give or take. It also opens the window to cross globe connection. IoT, being an incredibly huge network of connected devices that allow data to be easily shared and retrieved surpassing the boundaries of time, region, and space, gives rise to the concept of ubiquitous or pervasive computing, which integrates the features of the Internet, digital, and communication sectors into one technology, thereby enabling the machines to become truly independent. This work is a comprehensive survey on the IoT paradigm highlighting its features and applications. It introduces the reader to basic concepts of AI and machine learning and then goes on to describe IoT using various examples, leading to the delivery of a complete picture of the world of AI-based IoT as of now.

The mechanisms based on the distributed environment have become an obvious choice for solutions, while they have not been limited only to a specific domain (i.e., crypto-currency). Rather, it has influenced other industries to develop robust privacy and security solutions, such as smart houses, smart electrical grids, smart agriculture, smart health care, smart transportation, etc. These Cyber-Physical Systems heavily depend on IoT-based smart devices that constitute a networked system of devices dependent on each other for the smooth operation of the overall system. Hence, security and privacy have become an integral part of all the architectural frameworks they operate in. The adoption of these architectures, such as the Internet of Things (IoT), Internet of Cyber-Physical Things (IoCPT), Cyber-Physical Systems (CPSs), and Internet of Everything (IoE), has reinforced the need to develop solutions based on a distributed environment. Distributed ledger technology, i.e., Blockchain, has taken the lead and may support the development of solutions with robust privacy and security. We provide an updated review of authentication mechanisms developed on blockchain technology that enforce decentralized architectures. We discuss the security issues regarding the authentication of these IoT-enabled smart devices. We evaluate and analyze the study of the proposed literature schemes that pose authentication challenges in terms of computational costs, communication overheads, and models applied to attain robustness. Hence, lightweight solutions for managing, maintaining, processing, and storing authentication data of IoT-enabled assets are a must. From an integration perspective, cloud computing has provided strong support. In contrast, decentralized ledger technology, i.e., Blockchain, and lightweight cryptosystems are the areas for much more to explore. Finally, we discuss the future research challenges, which present an improvement standpoint to help address the ambiguities.

This article focuses on prospective applications of the Internet of Things. The Internet of Things (IoT) refers to the interconnected network of physical entities “things” equipped with sensors, software, and various other technologies to facilitate data exchange with other devices and systems over the Internet. As the IoT continues to develop as the next stage in the development of the Internet, it is essential to identify the many possible application areas of IoT and the research problems linked to these applications. The Internet of Things (IoT) is anticipated to permeate almost all facets of everyday life, including smart cities, healthcare, smart agriculture, logistics, retail, smart living, and smart surroundings. Despite significant advancements in IoT enabling technology in recent years, various issues still need attention. The IoT notion, stemming from diverse technologies, is likely to provide several research hurdles. The extensive nature of IoT, impacting almost all aspects of our life, makes it a crucial subject for study across numerous related disciplines, including information technologies and computer science. Consequently, IoT is facilitating new avenues for study exploration. This study delineates the current advancements in IoT technology and examines prospective applications and research obstacles.

Internet of Things is coming to critical missions such as battlefield, border patrol, search and rescue, critical structure monitoring and surveillance, etc. Internet of Things (IoT) in Critical Missions or Internet of Mission-Critical Things (IoMCT) is propelled by the convergence of sensing, communication, computing, and control. To support IoMCT, the mission-critical networks will need to be flexible and interactive, and still work despite limited bandwidth, intermittent connectivity and with a large number of devices on the network. The focus of IoMCT is to improve surveillance utilizing a network, not fusion of disparate sensor products. Such adaptation, management, and re-organization of information sources, devices, and networks must be accomplished almost entirely autonomously, in order to avoid imposing additional burdens on the humans, and without much reliance on support and maintenance services.

The recent trend in the Internet of Things (IoT) is bringing innovations in almost every field of science. IoT is mainly focused on the connectivity of things via the Internet. IoT’s integration tools are developed based on the Do It Yourself (DIY) approach, as the general public lacks technical skills. This paper presents a thermal comfort system based on tasks allocation mechanism in smart homes. This paper designs and implements the tasks allocation mechanism based on virtual objects composition for IoT applications. We provide user-friendly drag and drops panels for the new IoT users to visualize both task composition and device virtualization. This paper also designs tasks generation from microservices, tasks mapping, task scheduling, and tasks allocation for thermal comfort applications in smart home. Microservices are functional units of services in an IoT environment. Physical devices are registered, and their corresponding virtual objects are initialized. Tasks are generated from the microservices and connected with the relevant virtual objects. Afterward, they are scheduled and finally allocated on the physical IoT device. The task composition toolbox is deployed on the cloud for users to access the application remotely. The performance of the proposed architecture is evaluated using both real-time and simulated scenarios. Round trip time (RTT), response time, task dropping and latency are used as the performance metrics. Results indicate that even for worst-case scenarios, values of these metrics are negligible, which makes our architecture significant, better and ideal for task allocation in IoT network.

The Internet of Things (IoT) is a framework of interconnected computing devices mechanical and digital machines, internationally identifiable physical objects (or things) or people that are have unique identity and the ability to transfer data over a network without human-to-human or human-to-computer interaction., their combination with the Internet, and their representation in the digital world. The accessibility and availability of cheap components of IoT devices enables a extensive range of applications and provide smart environments. These devices perform actuating and sensing tasks and identified through unique addresses. The IoT devices are connected to the Internet and expected to use the Constrained Application Protocol (CoAP) at the application layer as a main web transfer protocol. Message Queuing Telemetry Transport (MQTT) does not enforce the use of a particular security approach for its applications, but instead leaves that to the application designer. Therefore, IoT solutions can be based on application context and specific security requirements. MQTT is a Client Server publish/subscribe messaging transport protocol. It is lightweight, open, uncomplicated, and designed to make implementation more easier. These characteristics of MQTT make it perfect for use in most of the situations, including communication in Machine to Machine (M2M) and Internet of Things (IoT). In IOT there is major use of Wireless Sensor Networks (WSN) which connects virtual world to physical world. In this paper focus is given to application layer of IOT. In application layer two important protocols are MQTT and CoAP. Security mechanism is proposed in the paper for these protocols.

In recent times, a massive amount of smart devices or objects are connected that enhances the scale of the digital world. These smart objects are referred as “things” or physical devices that have the potential to sense the real-world physical objects, collect the data, and network with others. The objects are connected through the internet, which crafts the terminology of Internet of Things (IoT). IoT has been developed and become the center of consideration due to the novelty of embedded device and a rapid enhancement in its number. This increase is resulting in the creative applications of smart environments. Smart transportation is a central stake for the quality of life of citizens in smart environment. Smart transportation involves the use of devices and sensors in the control system of vehicle; for example navigation system of cars, traffic signal management system, number recognition system and speed monitoring system. In this research article, we propose architecture for smart transportation system using Big Data analytics, in order to achieve real time processing and facilitate a friendly communication in the environment of IoT based smart transportation. The proposed architecture is a 3-phase scheme which is responsible for the organization and management of Big Data, real-time processing of Big Data and service management. The proposed architecture is a generic solution for the smart transportation planning using real time Big Data processing. The proposed scheme is realized using Spark over single node Hadoop setup with various input libraries. A huge amount of data from different authentic and reliable sources is measured to validate the proposed architecture. In addition, the effectiveness of proposed scheme also highlighted with regard to throughput.

Since the Internet of Things (IoT) will be entwined with everything we use in our daily life, the consequence of security flaws escalates. Smart objects will govern most of the home appliances and car engines yielding potential disaster scenarios. In this context, successful attacks could lead to chaos and scary scenarios (www.darkreading.com). Unprotected personal information may expose sensitive and embarrassing data to the public and attacks may threaten not only our computers and smart devices, but our intimacy and perhaps our lives too. Because persons and objects will be bonded with each other, user consent becomes critical. Therefore, thing, object, and user Identity will be the focus of future IoT security solutions, yielding a Trust, Security, and Privacy (TSP) paradigm, which may constitute the Achilles' heel of IoT. While security issues are quite straightforward, mainly from background knowledge, privacy issues are far more complex. Privacy constitutes a rather challenging task, even for the m...

Internet of Things has given us a new epoch of computing technology. As we know that Internet, a rebellion innovation has transformed everything, Internet of Things has made a hope for excellent future of Internet with Machine-Machine type of communication in addition. Thoughts of creation that correlates a different means of considering the events with invented concepts that avail the possibilities proposed by new approaches in intelligent ways. Framing an intelligent environment depends on smart education system, smart traffic management system, smart vehicle management system, smart waste management system, industrial control, smart agriculture etc. Today, safety on roads, cleanliness in residential areas, security at home has become an essential component in our daily life. So there is a necessity to avail new approach of innovative technologies based on Internet of Things to solve the environmental problems. In this paper we surveyed some of these problems and suggested various executable plans also. The actualization of smart sensing and transferring of data has offered a significant assurance for building the blueprints. This review paper has also shown that it is possible and affordable to construct these smart systems based on Internet of Things (IoT). We have studied various blueprints which can sense unforeseen happenings such as landslides, traffic jam, accidents, etc. using different sensors and demonstrate the facts accumulated on LED display. Observational outcomes have shown good agreement with the hypothetical statements.

Recently, IoT (Internet of Things) security is a critical issue while IoT is a big trend where a huge number of devices would be connected to the Internet. We focus on protecting physical devices from illegal access by intruders and give basic analysis for fundamental gaps between physical devices and embedded IoT softwares. We clarify that the critical difficulty in IoT security is implementing both of device functions and IoT functions on a same physical device. We also propose the IoT Agent Platform mechanism to separate IoT functions from physical devies and to run isolated IoT functions on cloud environment. The mechanism is based on the Dripcast which is a transparent programming framework for IoT devices where we don't care about communication, server-side programming nor database, at all. The Dripcast provides a very simple and easy development model which is a key for device vendors to develop physical devices to use IoT functions.

Solving Flexible Job Scheduling Problem (FJSP) under disruptions and unplanned events has achieved more attention in many researches. Today, the internet of things (IoT) is being implemented everywhere which is of human concern like smart city, smart environment, security, smart business process, smart agriculture, home automation and healthcare. Our objective in this work is to investigate the impact of emerging Internet of Things (IoT) on smart modern manufacturing to specially face Breakdown. An improved multi agent particle swarm optimization is presented and implemented on physically distributed system composed of embedded systems to solve the FJSP under machine breakdowns. We address also IoT challenges related to minimizing communication overheads.