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Ibrahim Al-Shourbaji
Researcher at Jazan University
Publications - 27
Citations - 622
Ibrahim Al-Shourbaji is an academic researcher from Jazan University. The author has contributed to research in topics: Computer science & Artificial neural network. The author has an hindex of 7, co-authored 21 publications receiving 426 citations. Previous affiliations of Ibrahim Al-Shourbaji include University of Hertfordshire.
Papers
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Journal ArticleDOI
Survey of main challenges (security and privacy) in wireless body area networks for healthcare applications
TL;DR: This paper reviewed WBAN communication architecture, security and privacy requirements and security threats and the primary challenges in WBANs to these systems based on the latest standards and publications and covers the state-of-art security measures and research.
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Design and evaluation of a hybrid system for detection and prediction of faults in electrical transformers
TL;DR: A hybrid system based on Genetic Neural Computing (GNC) for analyzing and interpreting the data derived from the concentration of the dissolved gases and generates the necessary decision rules to assist the system’s operator in identifying the exact fault in the transformer and its fault status.
Proceedings ArticleDOI
Mobile Cloud Computing: Challenges and Future Research Directions
TL;DR: In this work, the main challenges and issues related to MCC are outlined, the recent work and countermeasure solutions that are proposed by researchers to counter the challenges and crucial open research and issues that direct future research is highlighted.
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A Study of Cyber Security Awareness in Educational Environment in the Middle East
TL;DR: The results reveal that the participants do not have the requisite knowledge and understanding of the importance of information security principles and their practical application in their day-to-day work.
Journal ArticleDOI
A novel methodology towards a trusted environment in mashup web applications
TL;DR: A client side mashup security framework to ensure that the sources for mashup applications are tested and secured against malicious intrusions that is based on risk analysis and mashup source classification that will examine, analyze and evaluate the data transitions between the server-side and the client-side.