CISO & Cybersecurity Consultant to Taif University President

Dr. Mohammad Dahman Alshehri is a Cybersecurity Consultant for the President of Taif University, Chief Information Security Officer (CISO) and Assistant Professor of Computer Science (AI-Based Cybersecurity) at Taif University, Saudi Arabia, He received his PhD in Artificial Intelligence of Cybersecurity for the Internet of Things (IoT) from the University of Technology Sydney, Australia. He developed 6 smart novel algorithms for IoT to reinforce Cybersecurity with AI that is able to detect the various behaviours of cyberattacks and provide a full security and protection platform for the IoT from the most harmful cyberattacks. Furthermore, he received two Patents for AI-Based Cybersecurity and IoT, and he published more than 60 publications in high-ranked international journals, top-tier conferences, and chapters of books, also he received a number of international and national awards and prizes. He is an IEEE Senior Member (SMIEEE), an Ambassador of Emerging Technologies at Stanford University, US, and a Fellow of the Higher Education Academy (FHEA), UK. His main current research interest lies in the areas of Cybersecurity, Artificial Intelligence, Internet of Things (IoT).

Abstract:

Healthcare field is one of the most important fields that related to our lives. Essentially, healthcare systems are struggling with many cyberattacks that cause disruption of the vital healthcare systems. This is an innovation system and method for the prevention of cyberattacks in real-time systems using artificial neural networks (ANN) for healthcare field. Technically, the system for prevention of cyberattacks in real-time systems using ANN comprises of a long-short term memory (LSTM) recurrent neural network module to detect the Black Hole attacks, Gray Hole attacks, an ANN wavelet-based neural network module to detect the Wormhole attacks, a LSTM recurrent neural network module to detect the Denial of Service attacks. Moreover, the innovation is using to protect healthcare systems form the most harm cyberattacks such as ransomware. This innovated patent for prevention of cyberattacks in real-time systems using ANN wherein the analysis of the potential cyberattacks comprises steps of: decompiling the potential cyberattacks within the isolation hypervisor; determining that the potential cyberattacks corresponds to actual cyberattacks; determining a signature unique to the actual cyberattacks; storing the signature unique to the actual cyberattacks; tracing a route path of the actual cyberattacks and determining a source of the actual cyberattacks.