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This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering
Amjad Gawanmeh
University of Dubai
Computer Science & IT Electrical & Electronics Engineering

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Journal : International Journal of Electrical and Computer Engineering

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A trust-based authentication framework for security of WPAN using network slicing Sazia Parvin; Amjad Gawanmeh; Sitalakshmi Venkatraman; Ali Alwadi; Jamal N. Al-Karaki; Paul D. Yoo
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp1375-1387

Abstract

New technologies bring along many challenges including security and privacy. Wireless personal area networks (WPANs) are characterized by limited energy resources and computing power that calls for lightweight security mechanisms in these networks as a mandatory requirement. In this paper, a lightweight trust-based framework for node authentication in WPAN is proposed. Our main objective is to minimise the effort in distinguishing valid requests of trustworthy nodes from invalid requests of malicious nodes that can result in network compromises. We achieve this through network slicing which divides the network into virtually primary and secondary networks. The proposed framework has three-fold benefits. First, it authenticates nodes’ requests based on a novel method of trust value calculation. Second, the framework maintains energy efficiency while authenticating nodes’ requests to access WPAN resources. Finally, the framework provides a solution for biasing problem that can arise due to unexpected behaviour of malicious users in WPANs. The framework efficacy is illustrated on a case study to shown how it can accurately capture trust relations among nodes while preventing malicious behavior.
Big data analytics and internet of things for personalised healthcare: opportunities and challenges Sitalakshmi Venkatraman; Sazia Parvin; Wathiq Mansoor; Amjad Gawanmeh
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp4306-4316

Abstract

With the increasing use of technologies and digitally driven healthcare systems worldwide, there will be several opportunities for the use of big data in personalized healthcare. In addition, With the advancements and availability of internet of things (IoT) based point-of-care (POC) technologies, big data analytics and artificial intelligence (AI) can provide useful methods and solutions in monitoring, diagnosis, and self-management of health issues for a better personalized healthcare. In this paper, we identify the current personalized healthcare trends and challenges. Then, propose an architecture to support big data analytics using POC test results of an individual. The proposed architecture can facilitate an integrated and self-managed healthcare as well as remote patient care by adapting three popular machine learning algorithms to leverage the current trends in IoT, big data infrastructures and data analytics for advancing personalized healthcare of the future.
Co-Authors Ali Alwadi Jamal N. Al-Karaki Paul D. Yoo Sazia Parvin Sazia Parvin Sitalakshmi Venkatraman Sitalakshmi Venkatraman Wathiq Mansoor