Dr. Khalid Mahmood
National Yunlin University of Science and Technology
Research areas: Computer Science · Computer Networks and Communications · Advanced Authentication Protocols Security · Cryptography and Data Security · User Authentication and Security Systems
0000-0001-5046-7766
About
Khalid Mahmood received the Ph.D. degree in computer science from the International Islamic University, Islamabad, Pakistan, in 2018. He is currently working as an Associate Professor at the Future Technology Research Center, National Yunlin University of Science and Technology, Yunlin, Taiwan. Earlier, he also served as a Faculty Member with COMSATS University Islamabad, which is ranked # 1 in the IT category. He has published more than 70 SCI/E indexed articles and has been cited more than 1700 times. He is an approved supervisor by the Higher Education Commission of Pakistan. He has supervised more than 15 graduate students in their research. His research interests include design and development of lightweight authenticated and key agreement solutions for diverse infrastructures like smart grid, the Internet of Drones (IoD), the Internet of Things (IoT), vehicular ad hoc networks (VANET), mobile edge computing, and blockchain. In 2017, considering his research, Pakistan Council for Science and Technology granted him the Prestigious Young Productive Scientist Award, while affirming him among Top Productive Computer Scientist in Pakistan.
Employment
-
National Yunlin University of Science and Technology Assistant Professor2022 - 2023
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (131)
- FLSDF: A Federated Learning-Based Secure and Dynamic Data Fusion approach for IoT-based edge computing environments Save
- An Anonymous and Efficient Key Agreement Protocol for Secure Surgeon-Robot Interaction Over Tactile Internet Save
- Federated Metalearning-Driven Self-Organizing Maps for Edge-Based Privacy-Preserving Intrusion Detection in Industrial IoT Save
- A Privacy Preserving Federated Learning Framework for Securing Consumer Autonomous Vehicles Against AI-Enabled GPS Spoofing Attacks Save
- Conv-MTD: A CNN Based Multi-Label Medical Tubes Detection and Classification Model to Facilitate Resource-Constrained Point-of-Care Devices Save
- PUF-Enabled Key-Exchange Protocol for Vehicular Ad-Hoc Networks Save
- XAI-EdgeSFL: Explainable Edge Intelligence With Adaptive Intrusion-Resilient Split Federated Learning for Consumer Healthcare Ecosystems Save
- Digital Twin-Enabled Context-Aware Authentication Protocol for IoT-Based Healthcare Applications Save
- A Lightweight Authentication Scheme for Securing Patient Information in the Internet of Medical Things Environment Save
- A Digital Twin-Assisted Federated Learning Framework for GPS Spoofing Detection in Connected and Autonomous Vehicles Save
- A Lightweight and Secure Key Exchange Protocol for fortifying Home Area Network in Smart Grid Save
- A Robust Tamper-Resistant and Location-Aware Authentication Protocol for Securing Charging Services in V2G Environments Save
- AI-Driven Energy-Efficient Load Balancing in Hybrid Edge-Cloud Architectures for Renewable Energy Networks Save
- Adaptive Split Federated Learning With Behavioral Digital Twins and Multi-Head Temporal Networks for Internet of Vehicles Security Save
- Always On Trust for Remote Cardiac Monitoring: Quantum Safe Authentication With One Time PUFs and Edge Anomaly Screening Save
- An anonymous and secure authentication protocol for unmanned aerial vehicle-assisted and radio frequency identification-based vehicular Ad Hoc Networks Save
- Blockchain-enhanced Secure RFID Authentication for Anti-counterfeiting in Pharmaceutical Supply Chains Save
- CIWGS-FedMed: Channel-Importance Weighted Gradient Sparsification for Communication Efficient Federated Medical Image Segmentation Save
- DroneSec: Efficient and Secure Communication for Resource-Constrained Drones in IoD Systems Save
- ESCA-Net: Knowledge-Guided Encoder-Shared Classification and Auxiliary Segmentation Network for Multi-Label Catheter Malposition Assessment in Chest Radiographs Save