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The Internet of Things (IoT) continues to attract attention in the context of computational resource growth. Various disciplines and fields have begun to employ IoT integration technologies in order to enable smart applications. The main difficulty in supporting industrial development in this scenario involves potential risk or malicious activities...
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... nature of the interconnected structure of IoT systems is one of the major reasons causes of risks of malicious attacks [19]. As shown in Figure 2, specific attacks are designed for each layer of the IoT architecture. According to the literature, the typical method for ensuring security is ineffective, especially when it comes to user safety in IoT systems [20]. ...
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Citations
... This consensus mechanism greatly improves the system's overall security posture while also reducing the possibility of one single point of failure. The interconnection of nodes across different geographical regions defines distributed systems, which present a variety of security challenges such as attacks involving denial-of-service, illicit entry, and data modification [3]. Conventional security measures frequently find it difficult to sufficiently address these issues. ...
This study examines the revolutionary potential of the blockchain within distributed network security, emphasizing decentralized control of identities, efficiency of transactions, and scale. The capacity analysis demonstrated the system's flexibility by sustaining a respectable transaction speed as the total number of nodes rose, using a thorough setup for experimentation. Confirmation times, a critical performance indicator for transaction efficiency, showed how responsive the system had been with average assurance times under different transaction loads fluctuating between 12 to 21 seconds. Strong security was demonstrated by the decentralized identification management algorithm, which successfully confirmed user identities and stopped unwanted access attempts. Inspired by related research, such as studies on Internet of Things (IoT) applications, electric power system cooperation, and drone electrical charging infrastructure, our work adds to the growing body of scholarship on applications for blockchain technology. Our approach stands out from the crowd thanks to comparison with previous research that emphasizes the importance of autonomous identity management in given system security. This research offers practical implications for healthcare, finance, along with energy sectors, as well as useful insights to feed industries that depend on autonomous systems. Our study adds significant information and insights that will help shape the bitcoin blockchain's role in improving safety and productivity in interrelated systems as it continues to influence the digital future.
... These operators were created in an effort to draw in additional non-local, fractal-behaving natural problems. Many research fields, such as biology [23][24][25], engineering [26,27], and many more, as can be found in [28][29][30], used differential equation models. Various approaches are explored in the literature to discuss the behaviors of these models, including the generalized Kudryashov method [31,32], the reproducing kernel algorithm [33], and various other approaches [34,35]. ...
... In Ghana's public tertiary institutions, addressing these challenges will help libraries adapt their services to better meet user needs and foster a more inclusive and efficient digital environment (Falayi et al., 2023). However, in the face of the myriad benefits possessed by the digital transformation agenda in many areas of the global economy, including the West African sub-region, specifically Ghana, there is seemingly opposition from some sections of the population. ...
The chapter presents an IoT adoption framework for improving library management practices in Ghana's public tertiary institution. The internet of things (IoT) has revolutionized various industries, including libraries. The chapter aims to define a comprehensive framework that addresses the challenges and needs of Ghana's public higher education institution. Key areas where IoT integration can benefit library operations include resource monitoring, security, user experience, and data analytics. The framework also addresses potential obstacles and concerns related to privacy, security, and infrastructure limitations in the Ghanaian context. The chapter provides valuable insights for academic and administrative stakeholders on using IoT technologies to improve library services and knowledge dissemination in Ghana's public tertiary institution.
... It mitigates the volume of data via preprocessing and filtering. Also, it provides a high-performance and reliable infrastructure for IoT devices [83]. ...
... It eliminates the need for intermediaries, as the transactions are verified by multiple participants in the network [113]. A blockchain is the underlying technology behind cryptocurrencies, e.g., Bitcoin, but its applications extend beyond just financial transactions, including supply chain management, healthcare, and voting systems [83]. ...
The concept of smart cities, which aim to enhance the quality of urban life through innovative technologies and policies, has gained significant momentum in recent years. As we approach the era of next-generation smart cities, it becomes crucial to explore the key enabling technologies that will shape their development. This work reviews the leading technologies driving the future of smart cities. The work begins by introducing the main requirements of different smart city applications; then, the enabling technologies are presented. This work highlights the transformative potential of the Internet of things (IoT) to facilitate data collection and analysis to improve urban infrastructure and services. As a complementary technology, distributed edge computing brings computational power closer to devices, reducing the reliance on centralized data centers. Another key technology is virtualization, which optimizes resource utilization, enabling multiple virtual environments to run efficiently on shared hardware. Software-defined networking (SDN) emerges as a pivotal technology that brings flexibility and scalability to smart city networks, allowing for dynamic network management and resource allocation. Artificial intelligence (AI) is another approach for managing smart cities by enabling predictive analytics, automation, and smart decision making based on vast amounts of data. Lastly, the blockchain is introduced as a promising approach for smart cities to achieve the required security. The review concludes by identifying potential research directions to address the challenges and complexities brought about by integrating these key enabling technologies.
... Thanks to the large number of widely deployed and diverse sensing terminal devices, the IoT can timely and comprehensively obtain the dynamic situation of the target area, and can provide managers with good decision-making and feedback interaction. However, the IoT also faces greater security risks at the same time, as the large number of terminals poses challenges for the access management of the IoT gateway [8][9][10][11]. Specifically, if the terminals cannot be authenticated in a timely and reliable manner, the IoT may face problems of low efficiency and network attacks. Eventually, the network will be paralyzed, and sensitive data will be lost. ...
Internet of Things (IoT) technology has permeated into all aspects of today’s society and is playing an increasingly important role. Identity authentication is crucial for IoT devices to access the network, because the open wireless transmission environment of the IoT may suffer from various forms of network attacks. The asymmetry in the comprehensive capabilities of gateways and terminals in the IoT poses significant challenges to reliability and security. Traditional encryption-based identity authentication methods are difficult to apply to IoT terminals with limited capabilities due to high algorithm complexity and low computational efficiency. This paper explores physical layer identity identification based on channel state information (CSI) and proposes an intelligent identification method based on deep reinforcement learning (DRL). Specifically, by analyzing and extracting the features of the real received CSI information and a setting low-complexity state, as well as action and reward parameters for the deep neural network of deep reinforcement learning oriented to the scenario, we obtained an authentication method that can efficiently identify identities. The validation of the proposed method using collected CSI data demonstrates that it has good convergence properties. Compared with several existing machine-learning-based identity recognition methods, the proposed method has higher recognition accuracy.
