Relevant bibliographies by topics / Software Defined Network (SDN); IoT Security; SDN IoT Model

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Academic literature on the topic 'Software Defined Network (SDN); IoT Security; SDN IoT Model'

Author: Grafiati
Published: 4 June 2025
Last updated: 15 July 2025

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Journal articles on the topic "Software Defined Network (SDN); IoT Security; SDN IoT Model"

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Al-Shareeda, Mahmood A., Abeer Abdullah Alsadhan, Hamzah H. Qasim, and Selvakumar Manickam. "Software defined networking for internet of things: review, techniques, challenges, and future directions." Bulletin of Electrical Engineering and Informatics 13, no. 1 (2024): 638–47. http://dx.doi.org/10.11591/eei.v13i1.6386.

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Security networks as one of the biggest issue for network managers with the exponential growth of devices connected to the internet. Keeping a big and diverse network running smoothly and securely is no easy feat. With this in mind, emerging technologies like software defined networking (SDN) and internet of things (IoT) hold considerable promise for information service innovation in the cloud and big data era. Therefore, this paper describes the model of SDN and the architecture of IoT. Then this review does not only review the research studies in SDN-IoT but also provides an explanation of the SDN-IoT solution in terms of architecture, main consideration, model, and the implementation of SDN controllers for IoT. Finally, this review discusses the challenges and future directions. This paper can be used as a starting point for thinking about how to improve SDN-IoT security and privacy.
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Nazmul, Hossain, Zobayer Hossain Md, and Md. Alam Hossain Dr. "AN ONTOLOGICAL SECURITY FRAMEWORK TO SECURE THE SDN BASED IOT NETWORKS." American Journal of Agricultural Science Engineering and Technology 5, no. 1 (2021): 4–18. https://doi.org/10.5281/zenodo.4701563.

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The IoT (Internet of Things) is now a trendy technology with its numerous apps in multiple areas. It includes a heterogeneous amount of Internet and mutually linked devices. Since the IoT network is characterized by tiny assets that produce less energy and are more flexible, this number of machines is difficult to monitor. SDN (Software Defined Network) is a new network model that facilitates the creation and introduction of fresh networking abstractions, simplifies the management of network and facilitates network development. In this paper, by leveraging the fundamental characteristics represented by Software Defined Networks (SDN), we present an ontological security architecture for IoT networks. Our security architecture restricts access to independently verified IoT devices via the network. To secure the flows in the IoT network infrastructure, we introduced an extra layer and provide a lightweight protocol to authenticate IoT systems. Such an advanced strategy to protection containing IoT device authentication and allowing approved flows can assist secure IoT networks against malicious IoT devices and threats.
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Al Hayajneh, Abdullah, Md Zakirul Alam Bhuiyan, and Ian McAndrew. "Improving Internet of Things (IoT) Security with Software-Defined Networking (SDN)." Computers 9, no. 1 (2020): 8. http://dx.doi.org/10.3390/computers9010008.

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There has been an increase in the usage of Internet of Things (IoT), which has recently become a rising area of interest as it is being extensively used for numerous applications and devices such as wireless sensors, medical devices, sensitive home sensors, and other related IoT devices. Due to the demand to rapidly release new IoT products in the market, security aspects are often overlooked as it takes time to investigate all the possible vulnerabilities. Since IoT devices are internet-based and include sensitive and confidential information, security concerns have been raised and several researchers are exploring methods to improve the security among these types of devices. Software defined networking (SDN) is a promising computer network technology which introduces a central program named ‘SDN Controller’ that allows overall control of the network. Hence, using SDN is an obvious solution to improve IoT networking performance and overcome shortcomings that currently exist. In this paper, we (i) present a system model to effectively use SDN with IoT networks; (ii) present a solution for mitigating man-in-the-middle attacks against IoT that can only use HTTP, which is a critical attack that is hard to defend; and (iii) implement the proposed system model using Raspberry Pi, Kodi Media Center, and Openflow Protocol. Our system implementation and evaluations show that the proposed technique is more resilient to cyber-attacks.
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Hossain, Nazmul, Md Zobayer Hossain, and Md Alam Hossain. "An Ontological Security Framework to Secure the SDN based IoT Networks." American Journal of Agricultural Science, Engineering and Technology 5, no. 1 (2021): 4–18. http://dx.doi.org/10.54536/ajaset.v5i1.55.

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The IoT (Internet of Things) is now a trendy technology with its numerous apps in multiple areas. It includes a heterogeneous amount of Internet and mutually linked devices. Since the IoT network is characterized by tiny assets that produce less energy and are more flexible, this number of machines is difficult to monitor. SDN (Software Defined Network) is a new network model that facilitates the creation and introduction of fresh networking abstractions, simplifies the management of network and facilitates network development. In this paper, by leveraging the fundamental characteristics represented by Software Defined Networks (SDN), we present an ontological security architecture for IoT networks. Our security architecture restricts access to independently verified IoT devices via the network. To secure the flows in the IoT network infrastructure, we introduced an extra layer and provide a lightweight protocol to authenticate IoT systems. Such an advanced strategy to protection containing IoT device authentication and allowing approved flows can assist secure IoT networks against malicious IoT devices and threats.
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Asaithambi, Sasikumar, Logesh Ravi, Hossam Kotb, et al. "An Energy-Efficient and Blockchain-Integrated Software Defined Network for the Industrial Internet of Things." Sensors 22, no. 20 (2022): 7917. http://dx.doi.org/10.3390/s22207917.

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The number of unsecured and portable Internet of Things (IoT) devices in the smart industry is growing exponentially. A diversity of centralized and distributed platforms have been implemented to defend against security attacks; however, these platforms are insecure because of their low storage capacities, high power utilization, single node failure, underutilized resources, and high end-to-end delay. Blockchain and Software-Defined Networking (SDN) are growing technologies to create a secure system and to ensure safe network connectivity. Blockchain technology offers a strong and trustworthy foundation to deal with threats and problems, including safety, privacy, adaptability, scalability, and security. However, the integration of blockchain with SDN is still in the implementation phase, which provides an efficient resource allocation and reduced latency that can overcome the issues of industrial IoT networks. We propose an energy-efficient blockchain-integrated software-defined networking architecture for Industrial IoT (IIoT) to overcome these challenges. We present a framework for implementing decentralized blockchain integrated with SDN for IIoT applications to achieve efficient energy utilization and cluster-head selection. Additionally, the blockchain-enabled distributed ledger ensures data consistency throughout the SDN controller network and keeps a record of the nodes enforced in the controller. The simulation result shows that the proposed model provides the best energy consumption, end-to-end latency, and overall throughput compared to the existing works.
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Hatamleh, Hazem (Moh’d Said), As’ad Mahmoud As’ad Alnaser, Said S. Saloum, Ahmed Sharadqeh, and Jawdat S. Alkasassbeh. "PictureGuard: Enhancing Software-Defined Networking–Internet of Things Security with Novel Image-Based Authentication and Artificial Intelligence-Powered Two-Stage Intrusion Detection." Technologies 13, no. 2 (2025): 55. https://doi.org/10.3390/technologies13020055.

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Software-defined networking (SDN) represents a transformative approach to network management, enabling the centralized and programmable control of network infrastructure. This paradigm facilitates enhanced scalability, flexibility, and security in managing complex systems. When integrated with the Internet of Things (IoT), SDN addresses critical challenges such as security and efficient network management, positioning the SDN-IoT paradigm as an emerging and impactful technology in modern networking. The rapid proliferation of IoT applications has led to a significant increase in security threats, posing challenges to the safe operation of IoT systems. Consequently, SDN-IoT-based applications and services have been widely adopted to address these issues and challenges. However, this platform faces critical limitations in ensuring scalability, optimizing energy consumption, and addressing persistent security vulnerabilities. To overcome these issues, we proposed a secure SDN-IoT environment for intrusion detection and prevention using virtual blockchain (V-Block). Initially, IoT users are registered and authenticated to the shadow blockchain nodes using a picture-based authentication mechanism. After that, authenticated user flows validation was provided by considering effective metrics utilizing the Trading-based Evolutionary Game Theory (TEGT) approach. Then, we performed a local risk assessment based on evaluated malicious flows severity and then the attack graph was constructed using an Isomorphism-based Graph Neural Network (IGNN) model. Further, multi-controllers were placed optimally using fox optimization algorithm. The generated global paths were securely stored in the virtual blockchain Finally, the two agents in the multi-controllers were responsible for validating and classifying the incoming suspicious flow packets into normal and malicious packets by considering the operative metrics using the Dueling Deep Q Network (DDQN) algorithm. The presented work was conducted by Network Simulator-3.26 and the different performance matrices were used to itemize the suggested V-Block model based on its malicious traffic, attack detection rate, link failure rate, anomaly detection rate, and scalability.
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Wani, Azka, and S. Revathi. "Ransomware protection in IoT using software defined networking." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (2020): 3166. http://dx.doi.org/10.11591/ijece.v10i3.pp3166-3175.

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Internet of things (IoT) is the network of physical objects connected to provide various services. IoT is expanding rapidly, and is positively influencing many areas. The impact of IoT is evident in medical field, manufacturing units and livestock. The IoT is also vulnerable to many cyber threats, owing to its limited resources and battery operation. In contemporary times the security threats like DDoS, botnet malware, man in the middle, flood attacks and ransomware are affecting the smooth functioning of IoT. Ransomware has emerged as one of the biggest threat in cyber world. Ransomware is a type of malware that stops the access to files by encrypting them and decrypts the files only when a ransom is paid. The negligence towards the IoT ransomware can result in disastrous outcomes. In this paper, the growth of ransomware attacks for past few years is shown with special focus on ransomwares threatening IoT. A detection mechanism for IoT ransomware attack is presented that is designed after study of ransomware for IoT. The proposed model monitors the incoming IoT traffic through Software Defined Network (SDN) gateway. It uses policies framed in SDN controller for detection and alleviation of ransomware in IoT.
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Azka, Wani, and Revathi S. "Ransomware protection in loT using software defined networking." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (2020): 3166–75. https://doi.org/10.11591/ijece.v10i3.pp3166-3175.

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Internet of things (IoT) is the network of physical objects connected to provide various services. IoT is expanding rapidly, and is positively influencing many areas. The impact of IoT is evident in medical field, manufacturing units and livestock. The IoT is also vulnerable to many cyber threats, owing to its limited resources and battery operation. In contemporary times the security threats like DDoS, botnet malware, man in the middle, flood attacks and ransomware are affecting the smooth functioning of IoT. Ransomware has emerged as one of the biggest threat in cyber world. Ransomware is a type of malware that stops the access to files by encrypting them and decrypts the files only when a ransom is paid. The negligence towards the IoT ransomware can result in disastrous outcomes. In this paper, the growth of ransomware attacks for past few years is shown with special focus on ransomwares threatening IoT. A detection mechanism for IoT ransomware attack is presented that is designed after study of ransomware for IoT. The proposed model monitors the incoming IoT traffic through Software Defined Network (SDN) gateway. It uses policies framed in SDN controller for detection and alleviation of ransomware in IoT.
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Muthanna, Ammar, Abdelhamied A. Ateya, Abdukodir Khakimov, et al. "Secure and Reliable IoT Networks Using Fog Computing with Software-Defined Networking and Blockchain." Journal of Sensor and Actuator Networks 8, no. 1 (2019): 15. http://dx.doi.org/10.3390/jsan8010015.

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Designing Internet of Things (IoT) applications faces many challenges including security, massive traffic, high availability, high reliability and energy constraints. Recent distributed computing paradigms, such as Fog and multi-access edge computing (MEC), software-defined networking (SDN), network virtualization and blockchain can be exploited in IoT networks, either combined or individually, to overcome the aforementioned challenges while maintaining system performance. In this paper, we present a framework for IoT that employs an edge computing layer of Fog nodes controlled and managed by an SDN network to achieve high reliability and availability for latency-sensitive IoT applications. The SDN network is equipped with distributed controllers and distributed resource constrained OpenFlow switches. Blockchain is used to ensure decentralization in a trustful manner. Additionally, a data offloading algorithm is developed to allocate various processing and computing tasks to the OpenFlow switches based on their current workload. Moreover, a traffic model is proposed to model and analyze the traffic indifferent parts of the network. The proposed algorithm is evaluated in simulation and in a testbed. Experimental results show that the proposed framework achieves higher efficiency in terms of latency and resource utilization.
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Hang, Feilu, Linjiang Xie, Zhenhong Zhang, Wei Guo, and Hanruo Li. "Information Security Situation in Blockchain for Secure SDN Based on Big Data in Smart Communities." International Journal of Information Security and Privacy 16, no. 2 (2022): 1–19. http://dx.doi.org/10.4018/ijisp.308315.

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In the internet of things (IoT) and big data, the global information society is entering a new phase where consumers, networks, and perception devices work together more intimately. Software-defined networks (SDN) offer lower latency and massive connectivity for intelligent devices (IoT) for the internet of things. Smart communities are one of the most important applications of the blockchain. SDN technology is used to provide residents with smart services. Situational awareness for information security offers a distinct, high-level security perspective based on security alarm occurrences. However, contemporary information security warning data has become too complicated and varied than a simple analysis is almost impossible. In addition to enhancing IoT security's monitoring, emergency response, and forecasting capabilities, this article presents an IoT-assisted information security situation awareness framework (IoT-ISSAF). SDN model has been validated through simulation as being able to accurately assess the current state of network security in blockchain.
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Book chapters on the topic "Software Defined Network (SDN); IoT Security; SDN IoT Model"

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Karale, Ankita, Ram Kumar Solanki, Anand Singh Rajawat, S. B. Goyal, Yao Peiyu, and Weiming Chee. "Integrating Security in Software Defined Network (SDN) with IoT Enabled Fog Computing: A Paradigm Shift in Edge Computing." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-73318-5_24.

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Xu, Ronghua, Deeraj Nagothu, and Yu Chen. "AR-Edge: Autonomous and Resilient Edge Computing Architecture for Smart Cities." In Edge Computing - Architecture and Applications for Smart Cities [Working Title]. IntechOpen, 2024. http://dx.doi.org/10.5772/intechopen.1005876.

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With the rapid advancements in artificial intelligence (AI), the Internet of Things (IoT), and network communication technologies, recent years have witnessed a boom in smart cities that has dramatically changed human life and society. While many smart city applications rely on cloud servers, enabling comprehensive information fusion among users, smart devices, and service providers to provide diverse, intelligent applications, IoT networks’ high dynamicity and heterogeneity also bring performance, security, and interoperability challenges to centralized service frameworks. This chapter introduces a novel Autonomous and Resilient Edge (AR-Edge) computing architecture, which integrates AI, software-defined network (SDN), and Blockchain technologies to enable next-generation edge computing networks. Thanks to capabilities in terms of logically centralized control, global network status, and programmable traffic rules, SDN allows for efficient edge resource coordination and optimization with the help of artificial intelligence methods, like large language models (LLM). In addition, a federated microchain fabric is utilized to ensure the security and resilience of edge networks in a decentralized manner. The AR-Edge aims to provide autonomous, secure, resilient edge networks for dynamic and complex IoT ecosystems. Finally, a preliminary proof-of-concept prototype of an intelligent transportation system (ITS) demonstrates the feasibility of applying AR-Edge in real-world scenarios.
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Majhi, Sumita, and Pinaki Mitra. "Lightweight Cryptographic Techniques in 5G Software-Defined Internet of Things Networking." In Cryptography - Modern Theory and Practices [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.102984.

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Lightweight cryptography (LWC) is an area of cryptographic techniques with low computational complexity and resource requirements. There must be a reason for using it in Internet of Things (IoT) network with a strict resource constraints environment. The key features of a 5G network are low latency, high throughput, heterogeneous network architecture, and massive connectivity. A new area of network architecture called SDN-IoT comes into the picture to control and manage IoT devices in a network with low latency and high throughput. SDN helps to reprogram the network according to the application’s requirements. Also, higher mobile applications lead to higher data growth. SDN helps to secure, manage, and control the huge data in the network. SDN-IoT architecture divides the network into three layers: The infrastructure layer, the control layer, and the service or application layer. In this chapter, we are focusing on the LWC algorithms from different perspectives so that they will fit into different layers of SDN-IoT network. We will discuss all the pros and cons of implementing LWC algorithms in hardware and software environments and also, the different layers of the SDN-IoT network. We also discuss SDN security architecture and different performance metrics for LWC algorithms.
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Majid, Muhammad Imran, Faheem Yar Khuhawar, Karrar Muhammad, et al. "NFV and Secure Cognitive SDN for Educational Backbone Network Deployment." In Advances in Wireless Technologies and Telecommunication. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-2893-4.ch010.

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Software defined networks (SDN) and wireless cognitive radio networks (CRN) are examined within the context of dynamic spectrum management. The features include control and data plane separation, centralized control, adopting open-source standards, programmability, quality of service (QoS) management, and security. The transformative impact of network function virtualization (NFV) is explored with a perspective on its architecture and applications in SDN, internet of things (IoT), cloud computing, and blockchain. The security aspect of SDN with specific focus on mitigating denial-of-service (DoS) attacks and vulnerabilities associated with open flow protocol is also addressed. The cognitive-inspired security mechanisms adapt to evolving threats integrating machine learning (ML) and artificial intelligence (AI) based algorithms for dynamic threat detection and mitigation exemplified through case studies. Adoption of software-defined perimeter, zero trust, blockchain, and quantum-safe cryptography in future are discussed. Finally, SDN applications for IoT networks are discussed.
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Swami, Rochak, Mayank Dave, and Virender Ranga. "DDoS Attacks and Defense Mechanisms Using Machine Learning Techniques for SDN." In Security and Privacy Issues in Sensor Networks and IoT. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0373-7.ch008.

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Distributed denial of service (DDoS) attack is one of the most disastrous attacks that compromises the resources and services of the server. DDoS attack makes the services unavailable for its legitimate users by flooding the network with illegitimate traffic. Most commonly, it targets the bandwidth and resources of the server. This chapter discusses various types of DDoS attacks with their behavior. It describes the state-of-the-art of DDoS attacks. An emerging technology named “Software-defined networking” (SDN) has been developed for new generation networks. It has become a trending way of networking. Due to the centralized networking technology, SDN suffers from DDoS attacks. SDN controller manages the functionality of the complete network. Therefore, it is the most vulnerable target of the attackers to be attacked. This work illustrates how DDoS attacks affect the whole working of SDN. The objective of this chapter is also to provide a better understanding of DDoS attacks and how machine learning approaches may be used for detecting DDoS attacks.
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Sasikala, Dr C., and Nazeer Shaik. "REVOLUTIONIZING WIRELESS COMMUNICATION: EXPLORING SOFTWARE-DEFINED WIRELESS NETWORKING." In Futuristic Trends in Network & Communication Technologies Volume 3 Book 1. Iterative International Publisher, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bbnc1p1ch5.

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Software-Defined Wireless Networking (SDWN) represents a paradigm shift in wireless communication networks, leveraging the principles of Software-Defined Networking (SDN) to enhance network management, flexibility, and efficiency. This paper provides an in-depth exploration of SDWN's concepts, applications, challenges, and future prospects. The control plane and data plane separation, adaptation of SDN principles, centralized vs. distributed control strategies, and programmability advantages form the foundation of SDWN. Applications include dynamic spectrum management, quality of service optimization, virtualized network slices, enhanced security, Internet of Things (IoT) connectivity, and edge computing integration. However, challenges such as scalability, reliable communication, security vulnerabilities, interoperability, and energy efficiency must be addressed. The future of SDWN holds promise in 6G integration, emerging technology synergies, autonomous networking, evolved management tools, and industry collaboration. Through these avenues, SDWN is set to reshape wireless networks and drive innovation in the realm of wireless communication.
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Shafik, Wasswa. "Making Cities Smarter." In Advances in Wireless Technologies and Telecommunication. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-7998-9266-3.ch004.

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The internet of things (IoT) entails all devices that can get onto the internet. This is mainly because of the technological advancement. This exponential growth of IoT increases on the dense nodes with a huge data volume on the network that affect the collision and network congestion probabilities. This chapter presents a comprehensive description of the central and supporting innovations that are used to make cities smarter, focusing on the fifth generation (5G) IoT paradigm from a software-based network viewpoint. Furthermore, the main initiatives of international significance are discussed. Also, the chapter presents software-defined networking (SDN), IoT, and network function virtualization (NFV) challenges as it relates to the user privacy and security, IoT security, energy consumption, integration of IoT with subsystems, and architecture design. A segment of the top five future trends that are made and will make cities smarter is conclusively included.
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Nketia, Ivonne Kuma, Winfred Yaokumah, and Justice Kwame Appati. "A Comprehensive Review of Internet-of-Things (IoT) Botnet Detection Techniques." In Smart and Agile Cybersecurity for IoT and IIoT Environments. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-3451-5.ch003.

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This chapter conducts a comprehensive empirical review of internet of things (IoT) botnet detection to identify gaps in the literature. An empirical analysis of literature work related to IoT botnet detection is conducted. A state-of-the-art review of works done on IoT botnet detection is synthesized. This review is based on classifying the subcategories of IoT botnet detection, including honeypot and intrusion detection techniques, specifically host and network-based IDSs. This is further broken down into anomaly, signature, and hybrid-based approaches. Anomaly-based detections include machine learning techniques and deep learning techniques. Other detection methods include distributed techniques (software defined networking [SDN] and blockchain), graph theory approach, and domain name service (DNS) techniques. Finally, the chapter recommends future research directions in IoT security and the application of deep learning techniques.
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Shaik, Abdul Subhahan, and Nazeer Shaik. "SOFTWARE-DEFINED WIRELESS NETWORKING: BRIDGING THE GAP BETWEEN SDN AND WIRELESS EVOLUTION." In Futuristic Trends in Network & Communication Technologies Volume 3 Book 1. Iterative International Publisher, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bbnc1p1ch16.

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Wireless networking has evolved significantly over the years, from the early days of 1G to the upcoming era of 6G. However, traditional wireless networks still face limitations in terms of flexibility, resource management, and adaptability. Software-Defined Wireless Networking (SDWN) emerges as a solution to address these challenges by integrating the principles of Software-Defined Networking (SDN) with wireless communication environments. This paper provides a comprehensive overview of SDWN, covering its concepts, architecture, benefits, challenges, and real-world applications. The paper begins by explaining the fundamentals of SDN and how it contrasts with traditional networking. It then delves into the core concepts of SDWN, highlighting its components and architecture. The advantages of SDWN in network management, Quality of Service (QoS) enhancement, and adaptability are discussed, along with the challenges it introduces, such as security concerns and scalability issues. The integration of SDWN with emerging technologies like 6G, artificial intelligence, edge computing, and efforts towards standardization are explored as future prospects. Case studies demonstrate the practical implementations of SDWN in different domains, including smart cities, industrial IoT, and healthcare environments. The challenges and open issues associated with SDWN are also addressed, encompassing scalability, dynamic spectrum management, network resilience, legal and regulatory considerations, and ethical implications. In conclusion, Software-Defined Wireless Networking holds the potential to revolutionize wireless communication by providing central control, dynamic resource management, and adaptability. As it matures, SDWN is set to play a significant role in shaping the future of wireless networks.
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Oluwatimilehin, Odubola Abel, Aderinola Musefiu, Chukwuka Michael Oforgu, et al. "Off-Grid Photovoltaic Solar Design Systems for Improved Grid Performance." In Advances in Environmental Engineering and Green Technologies. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-9924-8.ch005.

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A solar powered system, often known as a photovoltaic (PV) system, is an electric power system that uses solar radiation to generate usable solar energy for household consumption. In this paper, the authors designed an off-grid energy distribution system, utilizing an artificial neural network (ANN) algorithm to build a model that predicts, on a monthly basis, the average daily global sun radiation on a horizontal region of ground base using meteorological data which include the earth's temperature, relative humidity, wind speed, rainfall and ambient air quality. The authors discussed the issues in implementing software defined network (SDN) in the energy distribution, energy demand response, energy optimization and real-time monitoring required for load balancing. The SDN integration offered solutions that renewable energy technology could bring in the future technology-based electricity network driven by automation, communication, and internet of things (IoT) connectivity in the off grid implementation.
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Conference papers on the topic "Software Defined Network (SDN); IoT Security; SDN IoT Model"

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Tselios, C., I. Politis, and S. Kotsopoulos. "Enhancing SDN security for IoT-related deployments through blockchain." In 2017 IEEE Conference on Network Function Virtualization and Software-Defined Networks (NFV-SDN). IEEE, 2017. http://dx.doi.org/10.1109/nfv-sdn.2017.8169860.

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