A5044760281- IoT and Edge/Fog Computing
- Blockchain Technology Applications and Security
- Anomaly Detection Techniques and Applications
- Cloud Computing and Resource Management
- Network Security and Intrusion Detection
- Advanced Algorithms and Applications
- Autonomous Vehicle Technology and Safety
- Smart Parking Systems Research
- Hate Speech and Cyberbullying Detection
- Industrial Technology and Control Systems
- Sentiment Analysis and Opinion Mining
- Advanced Malware Detection Techniques
- Fire Detection and Safety Systems
- User Authentication and Security Systems
- IoT Networks and Protocols
- Cryptographic Implementations and Security
- Misinformation and Its Impacts
- UAV Applications and Optimization
- Internet Traffic Analysis and Secure E-voting
- Traffic and Road Safety
Air University
2022-2025
Lebanese American University
2023
Abstract Fog computing is an emerging research domain to provide computational services such as data transmission, application processing and storage mechanism. consists of a set fog server machines used communicate with the mobile user in edge network. introduced cloud meet communication needs for Internet Things (IoT) devices. However, vital challenges this system are job scheduling, which solved by examining makespan, minimizing energy depletion proper resource allocation. In paper, we...
There is an exponential rise in the use of smartphones government and private institutions due to business dependencies such as communication, virtual meetings, access global information. These are attractive target for cybercriminals one leading causes cyber espionage sabotage. A large number sophisticated malware attacks well advanced persistent threats (APTs) have been launched on smartphone users. becoming significantly more complex, sophisticated, persistent, undetected extended...
Given the increasing frequency of network attacks, there is an urgent need for more effective security measures. While traditional approaches such as firewalls and data encryption have been implemented, still room improvement in their effectiveness. To effectively address this concern, it essential to integrate Artificial Intelligence (AI)-based solutions into historical methods. However, AI-driven often encounter challenges, including lower detection rates complexity feature engineering...
Multimodal hateful social media meme detection is an important and challenging problem in the vision-language domain. Recent studies show high accuracy for such multimodal tasks due to datasets that provide better joint embedding narrow semantic gap. Religiously not extensively explored among published datasets. While there a need higher on religiously memes, deep learning–based models often suffer from inductive bias. This issue addressed this work with following contributions. First, memes...
Autonomous driving is predicted to play a large part in future transportation systems, providing benefits such as enhanced road usage and mobility schemes. However, self-driving cars must be perceived safe drivers by other users contribute traffic safety addition being operationally safe. Despite efforts develop machine learning algorithms solutions for the of automated vehicles, researchers have yet agree upon single approach categorizing accurately detecting unsafe behaviors. This paper...
Many approaches have been used to secure the Internet of Things (IoT) deployments or applications in recent years. These enable security system complex IoT devices applications, which is basis applying practical algorithms detect device threats, related patterns, vulnerabilities. Day by day, small computing made many technological improvements at an advanced level, implements over Internet, named devices. The blockchain has recently introduced as alternative solution and challenging...