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Erschienen in: Neural Computing and Applications 1/2019

02.11.2018 | Machine Learning Applications for Self-Organized Wireless Networks

A secure cloud-based solution for real-time monitoring and management of Internet of underwater things (IOUT)

verfasst von: M. P. Gopinath, G. S. Tamizharasi, L. Kavisankar, R. Sathyaraj, S. Karthi, S. L. Aarthy, B. Balamurugan

Erschienen in: Neural Computing and Applications | Sonderheft 1/2019

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Abstract

Internet of underwater things (IoUT) is an emerging technique with widespread applications. In such type of systems, efficient and secure use of network resources remains to be a greater challenge. This is due to the reason that it works on the basis of a network of smart interconnected objects. This creates the necessity for energy-aware and secure communication techniques across IoUT environment. In order to solve this issue, in this paper, a secure cloud-based solution for real-time monitoring and management of IoUT across smart cities is provided. The proposed system mainly focuses on secure data transmission with lesser energy requirements. This makes smart cities to go green and efficient. The major contribution of the proposed system is divided into two parts: First, an energy-aware efficient framework for IoUT system is defined. Next, we define an enhanced attribute-based encryption scheme with effective user attribute management for secure data transmission across IoUT systems. The simulations are performed, and the results state that the proposed approach provides better security and privacy measures than the existing system. In future, this work could be extended to deal with increasing amount of complexity measures with increased user attributes.

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Metadaten
Titel
A secure cloud-based solution for real-time monitoring and management of Internet of underwater things (IOUT)
verfasst von
M. P. Gopinath
G. S. Tamizharasi
L. Kavisankar
R. Sathyaraj
S. Karthi
S. L. Aarthy
B. Balamurugan
Publikationsdatum
02.11.2018
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe Sonderheft 1/2019
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3774-9

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