Securing Fog Computing Networks: An Advanced Trust Management System Leveraging Fuzzy Techniques and Hierarchical Evaluation DOI Creative Commons
Shraddha Thakkar,

Jaykumar Dave

International Journal of Electrical and Electronics Engineering, Год журнала: 2024, Номер 11(12), С. 229 - 234

Опубликована: Дек. 31, 2024

This paper presents a Trust Management System (TMS) designed to counteract cyber-attacks in fog computing environments. The system integrates fuzzy AHP, hierarchical PROMETHEE methods, and ranking evaluate trust based on Quality of Service (QoS), Security (QoSec), economic factors. Tested against Replay, On-Off, Bad-mouthing, Ransomware attacks, the demonstrates high detection accuracy, with error rates between 3.50% 4.15%. results show that proposed TMS effectively enhances security evaluation networks.

Язык: Английский

Strategic Synergies between 5G and Beyond and Smart Grids DOI Open Access
Marina Martinelli, Alysson Mazoni, Flávia Luciane Consoni

и другие.

Опубликована: Июль 10, 2023

This article provides a comprehensive review of the intersection 5G technology and Beyond, Smart Grids, focusing on potential Vehicle-to-Fog as an industrial alternative for addressing energy efficiency challenges in data processing. study aims to investigate relevant articles patents understand collaborative between Grids. It explores how establish new regulatory standards within architectural framework facilitate decentralized processing remodel consumption patterns. The hypothesis suggests that architecture Grids can be most effectively applied through vehicular fogging powered by solar energy. A combined quantitative qualitative methodology guides exploration patents. concludes advocating embrace processing, emphasizing future deployment 6G These advancements significantly enhance context pave way innovations.

Язык: Английский

Процитировано

1

Modeling and Optimization of Vehicular Fog Network Towards Minimizing Latency DOI
Deep Chandra Binwal, Rajeev Tiwari, Monit Kapoor

и другие.

Mobile Networks and Applications, Год журнала: 2023, Номер unknown

Опубликована: Авг. 8, 2023

Язык: Английский

Процитировано

1

Energy‐efficient mechanisms for sustainable operations in vehicular fog networks: Challenges, state‐of‐the‐art, and future directions DOI

Jing Jiang

International Journal of Communication Systems, Год журнала: 2024, Номер 37(16)

Опубликована: Июль 11, 2024

Summary Vehicular fog networks (VFNs) improve vehicular communications by incorporating computing into the existing infrastructure. The integration of and communication results in development a diverse range novel applications services, including intelligent transportation systems real‐time data analytics. This paradigm has evolved as an innovative strategy that deals with load on cloudlet nodes, improves service response time during high‐demand periods, saves energy battery‐powered devices. VFN is realized offloading user workloads to devices, taking advantage underutilized computational power nearby vehicles. While holds great promise, its widespread adoption faces many challenges, ineffective energy‐latency tradeoff mechanisms optimal resource allocation strategies. study provides thorough analysis explores examines current approaches, suggests ways tradeoffs between latency, thereby optimizing network resources. offers constructive recommendations for enhancing establishing more robust VFNs.

Язык: Английский

Процитировано

0

5G-LRVN: Latency Reduction Framework for SDVN using Fog Computing DOI
Righa Tandon, Ajay Verma,

P. K. Gupta

и другие.

Опубликована: Авг. 23, 2024

Язык: Английский

Процитировано

0

Securing Fog Computing Networks: An Advanced Trust Management System Leveraging Fuzzy Techniques and Hierarchical Evaluation DOI Creative Commons
Shraddha Thakkar,

Jaykumar Dave

International Journal of Electrical and Electronics Engineering, Год журнала: 2024, Номер 11(12), С. 229 - 234

Опубликована: Дек. 31, 2024

This paper presents a Trust Management System (TMS) designed to counteract cyber-attacks in fog computing environments. The system integrates fuzzy AHP, hierarchical PROMETHEE methods, and ranking evaluate trust based on Quality of Service (QoS), Security (QoSec), economic factors. Tested against Replay, On-Off, Bad-mouthing, Ransomware attacks, the demonstrates high detection accuracy, with error rates between 3.50% 4.15%. results show that proposed TMS effectively enhances security evaluation networks.

Язык: Английский

Процитировано

0