On the Integration of Blockchain and SDN: Overview, Applications, and Future Perspectives

Rahman, Asheq; Montieri, Antonio; Kundu, Dipanjali; Karim, Md. Razaul; Islam, Md. Jahidul; Sara, Umme; Nascita, Alfredo; Pescapè, Antonio

doi:10.1007/s10922-022-09682-4

Cited by 34 publications

(16 citation statements)

References 160 publications

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“…Indeed, SDN controllers can manage the virtual machines running network software and processes by decoupling the data and control planes via the standard OpenFlow protocol which provides the remote-management API to accomplish this task. 57 Additionally, NFV optimizes the implementation of network facilities in the SDN-IoT ecosystem by making it more efficient in terms of low power consumption, optimized performance, and reduction of safety concerns. 58 Moreover, through the proper combination of these technologies, the (IoT-5G) network environment becomes more efficient in terms of energy usage, data protection, and load balancing.…”

Section: Sdn-iot With Nfv Executionmentioning

confidence: 99%

“…Despite being complimentary, NFV and SDN are not interdependent: SDN is the safest option for prompt control and orchestration of NFV. Indeed, SDN controllers can manage the virtual machines running network software and processes by decoupling the data and control planes via the standard OpenFlow protocol which provides the remote‐management API to accomplish this task 57 . Additionally, NFV optimizes the implementation of network facilities in the SDN‐IoT ecosystem by making it more efficient in terms of low power consumption, optimized performance, and reduction of safety concerns 58 .…”

Section: Proposed “Blocksd‐5gnet” Architecture For 5g Networkmentioning

confidence: 99%

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BlockSD‐5GNet: Enhancing security of 5G network through blockchain‐SDN with ML‐based bandwidth prediction

Rahman,

Khan,

Montieri

et al. 2024

Trans Emerging Tel Tech

Self Cite

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The fifth generation (5G) of mobile communications is the most exciting emerging technology for researchers and scientists to get the full benefit of a network system. However, 5G networks confront massive threats and vulnerabilities including protection, privacy, and secrecy. To face these challenges in the increasingly interconnected Internet of Things (IoT) scenario, we aim to leverage state‐of‐the‐art technologies as software defined networking (SDN) in conjunction with network function virtualization (NFV), blockchain, and machine learning (ML). Indeed, these technologies convey a robust and secure setting in the networking platform enabling to manage several criticalities related to security, privacy, flexibility, and performance. In light of these considerations, in this article, we propose the “BlockSD‐5GNet” architecture to efficiently improve the security of a 5G network and to exploit the combined advantages of Blockchain, SDN, NFV, and ML. In the proposed architecture, the SDN helps to manage the network by dividing it into data plane and control plane, while the Blockchain guarantees improved security and confidentiality. Therefore, the “BlockSD‐5GNet” architecture can both secure sensitive data and attain reliable data transfer within and between the 5G network‐infrastructure planes. Additionally, an ML module is integrated into the SDN controller to estimate network bandwidth and assist the administrator in taking effective decisions and satisfying high‐bandwidth demand. We assess the performance of the “BlockSD‐5GNet” architecture via an experimental evaluation performed in a simulation environment, and show the effectiveness of the proposed solution in comparison with baseline schemes. Finally, we also demonstrate the capability of different ML models in bandwidth prediction.

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Section: Sdn-iot With Nfv Executionmentioning

confidence: 99%

Section: Proposed “Blocksd‐5gnet” Architecture For 5g Networkmentioning

confidence: 99%

BlockSD‐5GNet: Enhancing security of 5G network through blockchain‐SDN with ML‐based bandwidth prediction

Rahman,

Khan,

Montieri

et al. 2024

Trans Emerging Tel Tech

Self Cite

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“…Motion pursuit data will reveal insights that might fundamentally alter how we now do medical procedures. When the next generation of surgical robots is driven by AI and large information analytics, three of the most promising AI systems—Alpha Go, IBM Watson, and ML algorithms—may be integrated into surgical robots [92] .…”

Section: ML Dl and Smart Healthcare: State Of The Artmentioning

confidence: 99%

Machine learning and deep learning-based approach in smart healthcare: Recent advances, applications, challenges and opportunities

Rahman,

Debnath,

Kundu

et al. 2024

AIMSPH

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<abstract> <p>In recent years, machine learning (ML) and deep learning (DL) have been the leading approaches to solving various challenges, such as disease predictions, drug discovery, medical image analysis, etc., in intelligent healthcare applications. Further, given the current progress in the fields of ML and DL, there exists the promising potential for both to provide support in the realm of healthcare. This study offered an exhaustive survey on ML and DL for the healthcare system, concentrating on vital state of the art features, integration benefits, applications, prospects and future guidelines. To conduct the research, we found the most prominent journal and conference databases using distinct keywords to discover scholarly consequences. First, we furnished the most current along with cutting-edge progress in ML-DL-based analysis in smart healthcare in a compendious manner. Next, we integrated the advancement of various services for ML and DL, including ML-healthcare, DL-healthcare, and ML-DL-healthcare. We then offered ML and DL-based applications in the healthcare industry. Eventually, we emphasized the research disputes and recommendations for further studies based on our observations.</p> </abstract>

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“…[77] Security in IoT Clouds An overview of common security issues of SDN-based IoT clouds. [78] Security and Privacy Survey on security and privacy issues of BC and SDN integration considering applications and challenges in real implementations. [79] Security in Intrusion Detection Systems…”

Section: Reference Target Domain Summarymentioning

confidence: 99%

“…Similarly, the survey presented in [78] presents an overview of the literature background on BC and SDN, with a broad presentation of BC-SDN integration discussing the benefits and limitations of BC-SDN approaches. In the survey, the authors address the key features of the BC-SDN ecosystem, the main security and privacy weaknesses of BC-SDN, and the recent integration of BC-SDN to new smart system applications (e.g., healthcare system, supply chain management, e-voting, etc.…”

Section: Reference Target Domain Summarymentioning

confidence: 99%

A Promising Integration of SDN and Blockchain for IoT Networks: A Survey

et al. 2023

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The state of computer network technologies has continually advanced at a rapid pace. Software Defined Networking (SDN) and Blockchain (BC) have emerged as complementary technologies providing support that facilitates greater security and greater network performance for many domains of application, including the Internet of Things (IoT) ecosystem, ideally resulting in an improvement in our collective quality of life. The proliferation of IoT devices, driven by a wide variety of use cases and its ubiquitous availability, combined with the emergence of SDN and BC, presents rich opportunities for various emerging research efforts. This paper presents a comprehensive survey of the studies in which BC and SDN have been integrated into the IoT ecosystem, referred to hereafter as BC-enabled Software-Defined IoT (BC-SDIoT). First, we discuss the motivations and drivers for integrating BC-enabled SDN and BC-SDIoT, as well as the benefits and drawbacks. Second, we categorize the relevant studies according to six key implementation objectives and ideas that combine BC, SDN, and IoT technologies to create smart, secure, and effective frameworks: Security, computing paradigms (edge and fog computing), trust management, access control & authentication, privacy, and networking. In the corresponding sections, we present the categories (i.e., problem domains) of the aforementioned novel taxonomy and discuss related studies (i.e., solutions) in depth. Finally, we outline potential major challenges, open issues, and future prospects that require further research attention and intensive endeavors for complete and ground-breaking frameworks to broaden newer research domains in BC-SDIoT. This survey paper may be a fruitful primer for a reader investigating the exploitation of BC in SDN and IoT ecosystems.

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On the Integration of Blockchain and SDN: Overview, Applications, and Future Perspectives

Cited by 34 publications

References 160 publications

BlockSD‐5GNet: Enhancing security of 5G network through blockchain‐SDN with ML‐based bandwidth prediction

BlockSD‐5GNet: Enhancing security of 5G network through blockchain‐SDN with ML‐based bandwidth prediction

Machine learning and deep learning-based approach in smart healthcare: Recent advances, applications, challenges and opportunities

A Promising Integration of SDN and Blockchain for IoT Networks: A Survey

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