Internet of Things Data Privacy and Security-Based on Blockchain Technology
Küçük Resim Yok
Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer International Publishing Ag
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The integration of Deep Extreme Learning Machine (D.E.L.M) and blockchain technology represents a paradigm shift in addressing security and privacy challenges within the Internet of Things (IoT), particularly in smart system environments. In this research, a blockchain-based smart system, enhanced by D.E.L.M, is proposed to fortify security, optimize energy consumption, and provide personalized user experiences. The decentralized nature of blockchain ensures tamper-resistant data storage, mitigating vulnerabilities associated with centralized authentication servers. The system's performance is evaluated through statistical measures during the training and validation phases, demonstrating high accuracy and minimal false predictions. This study contributes to advancing the understanding of blockchain and D.E.L.M synergies in the context of smart systems, offering a foundation for further exploration and innovation within IoT ecosystems. As smart systems become increasingly prevalent, the proposed system lays the groundwork for a more secure, adaptive, and privacy-conscious IoT landscape.
Açıklama
2nd International Conference on Forthcoming Networks and Sustainability in the AIoT Era (FoNeS-AIoT) -- JAN 27-29, 2024 -- Istanbul, TURKEY
Anahtar Kelimeler
Internet of Things (IoT), Blockchain, Deep Extreme Learning Machine (DELM), smart system, Security, Privacy, Decentralization
Kaynak
Forthcoming Networks and Sustainability in the Aiot Era, Vol 2, Fones-Aiot 2024
WoS Q Değeri
N/A
Scopus Q Değeri
Q4
Cilt
1036
