A5030015140- Data Management and Algorithms
- Human Mobility and Location-Based Analysis
- Age of Information Optimization
- Network Security and Intrusion Detection
- Internet Traffic Analysis and Secure E-voting
- Geographic Information Systems Studies
- Software Engineering Techniques and Practices
- Smart Agriculture and AI
- Retinal Diseases and Treatments
- Advanced MIMO Systems Optimization
- Retinal Imaging and Analysis
- Traffic Prediction and Management Techniques
- Brain Tumor Detection and Classification
- Anomaly Detection Techniques and Applications
- Indoor and Outdoor Localization Technologies
- Cognitive Radio Networks and Spectrum Sensing
- Context-Aware Activity Recognition Systems
- Advanced Malware Detection Techniques
- Software Engineering Research
- IoT and Edge/Fog Computing
- Advanced Software Engineering Methodologies
King Khalid University
2023-2025
Pir Mehr Ali Shah Arid Agriculture University
2013
Wilfrid Laurier University
2005-2006
American University of Beirut
2005
The adoption of cloud computing has become increasingly widespread across various domains. However, the inherent security vulnerabilities pose significant risks to its overall safety. Consequently, intrusion detection systems (IDS) play a pivotal role in identifying malicious activities within system. considerable volume network traffic data may contain redundant and irrelevant features that can impact classification performance classifier. In addition, complexity time consumption increase...
Cognitive Radio Ad-hoc Networks (CRAHNs) combines characteristics of ad-hoc networks with cognitive radios to facilitate a variety communication scenarios. However, these are subject persistent attacks from internal and external adversaries, such as Masquerading, Spoofing, Spying, Distributed Denial Service (DDoS). Existing deep learning models proposed counter suffer complexity, real-time processing limitations, lack network scalability. In addition, their limited IP tracing capabilities...
With the advent of GPS systems, location tracking has become an essential component fleet management systems. Reliable estimation each member is critical for optimum operation organizations such as police force, taxi-cab, and trucking companies. In this paper a framework modeling drivers in environments purposes proposed. The framework's goal to increase LTS's ability accurately answer queries about whereabouts its members past, present, future
In previous work we introduced the idea of user modeling as a means reducing uncertainty in location tracking human-controlled moving objects. We used name roving users (RU for short) to refer this subset paper discuss issue complexity model caused by variables with high number possible values. show how self organizing maps (SOM) could be classify values certain variable such that classes are - rather than actual calculating conditional probabilities child variables. support our proposed...
Summary form only given. Location tracking systems are discrete in nature location information about each moving object (MO) is sampled at certain points time. To determine the of a MO between reports or sometime future, we have to estimate that point time using already have. The sampling frequency could affect system's estimation accuracy as well operating costs. Poor also carry cost. objective maximize while minimizing In this paper, introduce novel idea user modeling improve both route...