Academic Profile

Abdullah Khan received his MS degree in Computer Science in 2025 from the University of Wah, Wah Cantt, Pakistan, with a final CGPA of 3.81/4.0, and his BS degree in Software Engineering in 2022 from COMSATS University Islamabad, Wah Campus, Pakistan. He has published research on CAN bus intrusion detection and deepfake voice detection, and has manuscripts under review in areas such as quantum neural networks and blockchain-based security. He has presented his work at international conferences, including ICETECC 2025. His research interests include AI security, deep learning, explainable AI (XAI), quantum computing, intrusion detection in autonomous vehicles, and medical imaging.

Editorial Roles

No Editorial Roles

This user currently does not serve as an editor for any ICCK journals.

ICCK Publications

Total Publications: 1
Open Access | Research Article | 02 January 2026
Enhancing Social Media Bot Detection with Cross-Feature Gating and Residual Learning
by
Abdullah Khan
,
Arooj Fatima
,
Ridda Jamil
,
Hassan Ahmed
,
Aini Saba
ICCK Transactions on Emerging Topics in Artificial Intelligence | Volume 3, Issue 1: 20-32, 2026 | DOI: 10.62762/TETAI.2025.791029
Abstract
The growing presence of malicious bot accounts on social media poses a threat to the authenticity of online communities, as they amplify misinformation, spread spam, and manipulate engagement. Reliable detection of these accounts is therefore essential to protect the integrity of platforms such as Instagram. This study introduces a deep learning–based detection framework built on the CrossGatedTabular (CGT) architecture, designed to learn complex patterns in user activity. To strengthen evaluation, two publicly available datasets of Instagram accounts were merged into a comprehensive benchmark representing diverse user behaviors. Natural language processing (NLP) was applied to refine text... More >
Graphical Abstract
Enhancing Social Media Bot Detection with Cross-Feature Gating and Residual Learning