Badiea Abdulkarem Mohammed on Muck Rack

Badiea Abdulkarem Mohammed

As seen in: MDPI
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Articles

Deep and Hybrid Learning Techniques for Diagnosing Microscopic Blood Samples for Early Detection of White Blood Cell Diseases

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By Tariq S Almurayziq, Ebrahim Mohammed Senan, Badiea Abdulkarem Mohammed, Zeyad Ghaleb Al-Mekhlafi
| MDPI
This is an early access version, the complete PDF, HTML, and XML versions will be available soon. Open AccessArticle by Tariq S.
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Efficient Authentication Scheme for 5G-Enabled Vehicular Networks Using Fog Computing

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By Zeyad Ghaleb Al-Mekhlafi, Selvakumar Manickam, Badiea Abdulkarem Mohammed, n Size
| MDPI
3.1. System Model Design According to novel research [11,34,35], we propose fog computing-based 5G-enabled vehicular networks, as shown in Figure 1. Our proposed architecture of the fog computing-based 5G-enabled vehicular networks consists of the following four components: one Trusted Authority (TA), some 5G-Base Stations (5G-BSs), some Fog Servers (FSs), and many vehicles. Trusted Authority (TA): It is assumed that the TA is a highly secure entity, which is reliable and independent.
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ANAA-Fog: A Novel Anonymous Authentication Scheme for 5G-Enabled Vehicular Fog Computing

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By Badiea Abdulkarem Mohammed, Selvakumar Manickam, Zeyad Ghaleb Al-Mekhlafi, Abdulaziz M. Alayba
| MDPI
Abstract : Vehicular fog computing enabled by the Fifth Generation (5G) has been on the rise recently, providing real-time services among automobiles in the field of smart transportation by improving road traffic safety and enhancing driver comfort. Due to the public nature of wireless communication channels, in which communications are conveyed in plain text, protecting the privacy and security of 5G-enabled vehicular fog computing is of the utmost importance.
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