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SASC: Secure and Authentication-Based Sensor Cloud Architecture for Intelligent Internet of Things

Authors :
Khalid Haseeb
Ahmad Almogren
Ikram Ud Din
Naveed Islam
Ayman Altameem
Source :
Sensors, Vol 20, Iss 9, p 2468 (2020)
Publication Year :
2020
Publisher :
MDPI AG, 2020.

Abstract

Nowadays, the integration of Wireless Sensor Networks (WSN) and the Internet of Things (IoT) provides a great concern for the research community for enabling advanced services. An IoT network may comprise a large number of heterogeneous smart devices for gathering and forwarding huge data. Such diverse networks raise several research questions, such as processing, storage, and management of massive data. Furthermore, IoT devices have restricted constraints and expose to a variety of malicious network attacks. This paper presents a Secure Sensor Cloud Architecture (SASC) for IoT applications to improve network scalability with efficient data processing and security. The proposed architecture comprises two main phases. Firstly, network nodes are grouped using unsupervised machine learning and exploit weighted-based centroid vectors for the development of intelligent systems. Secondly, the proposed architecture makes the use of sensor-cloud infrastructure for boundless storage and consistent service delivery. Furthermore, the sensor-cloud infrastructure is protected against malicious nodes by using a mathematically unbreakable one-time pad (OTP) encryption scheme to provide data security. To evaluate the performance of the proposed architecture, different simulation experiments are conducted using Network Simulator (NS3). It has been observed through experimental results that the proposed architecture outperforms other state-of-the-art approaches in terms of network lifetime, packet drop ratio, energy consumption, and transmission overhead.

Details

Language :
English
ISSN :
14248220
Volume :
20
Issue :
9
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.4ffa65e6d8bb4a86bc5119c0ba90b9a8
Document Type :
article
Full Text :
https://doi.org/10.3390/s20092468