Improving the Robustness of IoT-Powered Smart City Applications Through Service-Reliant Application Authentication Technique

Alsayaydeh, Jamil Abedalrahim Jamil; Irianto,; Ali, Mohanad Faeq; Al-Andoli, Mohammed Nasser Mohammed; Herawan, Safarudin Gazali

doi:10.1109/access.2024.3361407

Cited by 3 publications

(1 citation statement)

References 41 publications

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“…Saleem et al ( 2023) suggested an Adaptive Information-Centric Network utilizing Edge Computing Framework (AICN-ECF) to improve data traffic control and security in smart cities [17], [18]. The technology enhances user experience by combining edge computing with information-centric networking to optimize content distribution and caching.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Network-Based Analytical Model for Information-Centric Networking Implementation in 5G Communication

Alsayaydeh,

Shkarupylo,

Yusof

et al. 2024

Preprint

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Information-centric wireless computing (ICWC) improves 5G communication by enabling effective content distribution, decreasing network load, supporting flexible resource allocation, improving scalability, simplifying IoT and edge computing, and allowing content-aware services. "Information-Centric Networking" (ICN) involves creating and using a specific model to study the way it fits into 5G communication systems. 5G technology will enable real-time communications and seamless information management across all connected devices. Information-centric networking has emerged as a powerful facilitator for delivering scalable and realistic real-time applications regarding internet architecture, mobile infrastructures, and other communication devices. The widespread use of 5G applications requires a content delivery infrastructure with low latency, dependability, portability, and scalability. Traditional systems where consideration was given only to mobile device transmission, rather than fixed nodes, is inadequate because of the host-oriented approach and cannot cover all these objectives. For communication to be based purely on information resource IDs rather than the place or location of the resource, a new Internet paradigm known as "Information-Centric Networking" (ICN) is utilized. The issues above can be remedied by applying ICN principles. Because latency is the backbone of 5G networks, the goal is to permit minimal services such as network design, waiting time, automated systems, and speedier dissemination. To analyze data distribution in a network, we present an analytical technique that utilizes a Dynamic (ICN-AD) population, considering a wide range of variables, such as user density, communication speed, and the number of fixed nodes, to implement ICN for 5G communications. The suggested model allows us to calculate the diffusion time, transmission distance, and waiting time in closed form. Experiments have shown how high-speed and narrowband wireless communication technologies affect data transmission in 5G networks. Results show a notable transmission rate of around 91%, even with many users. Chance contacts between wireless nodes spread most data with minimum latency value (45ms).

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Section: Related Workmentioning

confidence: 99%

Dynamic Network-Based Analytical Model for Information-Centric Networking Implementation in 5G Communication

Alsayaydeh,

Shkarupylo,

Yusof

et al. 2024

Preprint

Self Cite

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Cyber epidemic spread forecasting based on the entropy-extremal dynamic interpretation of the SIR model

Kovtun,

Grochla,

Al-Maitah

et al. 2024

Egyptian Informatics Journal

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Robust Security Framework for IoT-Enabled Smart Cities: Leveraging Ensemble Machine Learning Techniques in Fog Computing Environments

Kumari,

Kaur

2024

Preprint

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In IoT domains, particularly those reliant on fog computing, possessing enhanced threat detection abilities is crucial. The decentralization and large number of devices, common in smart city environments, make these situations more challenging. Basic security controls are usually inadequate in a complicated and dynamic setting, which calls for innovative approaches to thwarting such intimidation. The gravity of these issues caused the authors to devise a hybrid approach incorporating Gradient Boosting Machines (GBM), Random Forest (RF), and AdaBoost algorithms. The hybrid algorithm combines the advantages of different approaches and minimizes the disadvantages of the individual approaches. The purpose of this research is to conduct an analysis of smart city security literature and assess whether ensemble models are more effective than individual models in the single model approach. The study used two datasets: the University of New South Wales-Network Based 15 (UNSW-NB15) and the Canadian Institute of Cybersecurity Intrusion Detection Systems 2017 (CICIDS2017). The performance metrics of the ensemble model were not only better than that of any single model but also achieved a respectable figure of 95.60% and even 96.67% accuracy on the UNSW-NB15 dataset and CICIDS – 2017, respectively. Key performance metrics showed significant improvements, including precision of 98.78% on UNSW-NB15 and 99.87% on CICIDS2017, recall rates of 99.13% and 99.85%, and F1-scores of 97.32% and 99.64%. These results validate the efficiency of ensemble techniques in safeguarding IoT-based smart city infrastructures, offering enhanced security mechanisms and improved response to evolving cyber threats.

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Improving the Robustness of IoT-Powered Smart City Applications Through Service-Reliant Application Authentication Technique

Cited by 3 publications

References 41 publications

Dynamic Network-Based Analytical Model for Information-Centric Networking Implementation in 5G Communication

Dynamic Network-Based Analytical Model for Information-Centric Networking Implementation in 5G Communication

Cyber epidemic spread forecasting based on the entropy-extremal dynamic interpretation of the SIR model

Robust Security Framework for IoT-Enabled Smart Cities: Leveraging Ensemble Machine Learning Techniques in Fog Computing Environments

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