Arshad Khan

About

Dr Arshad Khan received his Bachelor’s degree in Computer Science from the Agriculture University Peshawar, Pakistan, in 2013 and the MS degree in computer networks from the Qurtuba University of Information Technology (QUIT), Peshawar, Pakistan, in 2016, respectively. Dr. Arshad Khan received his Ph.D. in Computer Science from Auckland University of Technology, New Zealand in December 2023. His research spans a wide range of areas, including blockchain technology, machine learning, information systems, health analytics, cybersecurity, federated learning, cloud computing, IoT security, and medical data analytics. He has contributed to several interdisciplinary projects aimed at improving healthcare infrastructure, secure data sharing, and intelligent automation. Dr. Khan has authored peer-reviewed articles in high-impact journals such as Springer Nature, MDPI Sensors, and Electronics. He is an active member of the IEEE and regularly serves as a reviewer for IEEE conferences and journals.

Employment

• Shaanxi Normal University Research Assistant
  2017 - 2018
• Qurtuba University of Sciences and Information Technology Lecturer
  2015 - 2017

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (16)

• LiDAR Fusion-Based Optimized Path Selection for Autonomous Vehicles Using the Verification Model
  IEEE Internet of Things Journal 2026 DOI: 10.1109/JIOT.2026.3696527
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• Performance evaluation of intelligent hybrid approach and ant colony optimisation for early-stage diabetes prediction in e-Health applications
  Telematics and Informatics Reports 2026 DOI: 10.1016/j.teler.2026.100313
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• B-PhishQR—A blockchain-based framework for secure QR code verification against phishing attacks
  Telematics and Informatics Reports 2026 DOI: 10.1016/j.teler.2025.100289
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• HC-CSBA: Hash-Chained Collaborative Swarm-Based Batch Authentication for Secure UAV Communications in Satellite–Terrestrial Integrated Networks
  IEEE Open Journal of the Communications Society 2026 DOI: 10.1109/OJCOMS.2026.3720564
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• Hybrid approach for evaluating dynamic scheduling mechanisms in IoT cognitive sensors for enhanced network performance
  Scientific Reports 2026 DOI: 10.1038/s41598-025-29635-6
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• Integration of Sensing, Communication, and Computing for Satellite Consumer Applications
  IEEE Consumer Electronics Magazine 2026 DOI: 10.1109/MCE.2026.3658897
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• e-PrescripChain: A Secure and Patient- Centric Electronic Prescription System Using Blockchain and Federated Learning
  IEEE Communications Standards Magazine 2026 DOI: 10.1109/MCOMSTD.2025.3599152
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• Dual Attention-Driven Optimized YOLOV5 Framework for Accurate Fall Detection in Visual Monitoring Systems
  ICCK Transactions on Intelligent Systematics 2025 DOI: 10.62762/TIS.2025.559776
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• Privacy and Trust in Blockchain-Federated Intrusion Detection Systems: Taxonomy, Challenges and Perspectives
  Journal of Reliable and Secure Computing 2025 DOI: 10.62762/JRSC.2025.399812
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• BlockPres IPFS: performance evaluation of blockchain based secure patients prescription record storage using IPFS for smart prescription management system
  Cluster Computing 2025 DOI: 10.1007/s10586-024-05054-6
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