Amal Ajayan

About

I am a full-time Research Scholar at Amrita Vishwa Vidyapeetham, specializing in Cybersecurity and Digital Forensics. I hold both undergraduate and postgraduate degrees in Cyber Forensics from Mahatma Gandhi University, Kerala, where I graduated with academic distinction and secured a university rank during my master’s program. I have qualified the UGC-NET in Computer Science and Applications, reflecting a strong theoretical foundation and research readiness. My research interests focus on network security, digital forensics, threat intelligence, and cyber defence systems, with an emphasis on efficient and explainable security models. I have authored peer-reviewed research published in high-impact international journals and actively contribute to the academic community as a peer reviewer for Elsevier, Springer and IEEE journals. In parallel with research, I am deeply engaged in teaching and mentoring, with the long-term goal of building a research-driven academic career that integrates innovative security solutions with rigorous pedagogy and real-world relevance.

Employment

• Amrita Vishwa Vidyapeetham Research Fellow
  2024 - Present

Education

• Mohamed bin Zayed University of Artificial Intelligence Visiting Student
  2026 - 2026
• Amrita Vishwa Vidyapeetham Doctor of Philosophy (PhD)
  2024 - Present
• Mahatma Gandhi University M. Sc. Cyber Forensics
  2022 - 2024
• Mahatma Gandhi University B. Sc. Cyber Forensics
  2019 - 2022

Projects & Funding

Projects & funding information is unavailable.

Publications (9)

• FRX-IDS: An explainable intrusion detection framework with tamper-evident alert evidence logging
  Array 2026 DOI: 10.1016/j.array.2026.101089
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• Segmentation-Aware Hybrid CNN-ViT for Plant Leaf Disease Classification
  2026 International Conference on Recent Advancement in Electrical, Computer and Communication Technologies (IECCT) 2026 DOI: 10.1109/iecct68664.2026.11542021
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• A method for forensic-ready intrusion detection using explainable learning, prediction-aware graph modeling, and counterfactual analysis
  MethodsX 2026 DOI: 10.1016/j.mex.2026.103992
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• XNFT: Explainable network flow transformer for transparent detection of DDoS attacks in real-world networks
  Computer Networks 2026 DOI: 10.1016/j.comnet.2026.112224
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• Securing resource-constrained IoMT devices with an ultra-lightweight cryptographic framework
  PeerJ Computer Science 2026 DOI: 10.7717/peerj-cs.3715
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• DistilXIDS: Efficient, lightweight and explainable transformer-based language model for real-time network intrusion detection
  Neurocomputing 2026 DOI: 10.1016/j.neucom.2025.132398
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• PSO-GWO Optimized Encryption Algorithm for Secure Medical Image Transmission in IoT-Cloud Healthcare Systems
  KSII Transactions on Internet and Information Systems 2026 DOI: 10.3837/tiis.2026.02.008
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• Ensemble machine learning for proactive android ransomware detection using network traffic
  Scientific Reports 2026 DOI: 10.1038/s41598-026-38271-7
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• Enhancing IoT Resilience at the Edge: A Resource-Efficient Framework for Real-Time Anomaly Detection in Streaming Data
  CMES - Computer Modeling in Engineering and Sciences 2025 DOI: 10.32604/CMES.2025.065698
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