Dr. Surendra Tyagi

About

Dr. Surendra Tyagi is an Assistant Professor and researcher in Computer Science and Engineering, specializing in Internet of Things (IoT), Context-Aware Access Control, Artificial Intelligence/Machine Learning, and Smart-Home Security. He holds a Ph.D. in Computer Science and Engineering from IIT Jammu, with research focused on Context-Aware Access Control for IoT.He has 18+ years of experience in teaching, research, and technical leadership, with academic qualifications including a Ph.D. from IIT Jammu, M.Tech. from Delhi Technological University, and B.E. in Information Technology. His research work includes ontology-based access control, machine-learning-driven security, decentralized authorization, privacy in IoT, and intelligent decision-making systems.Dr. Tyagi has published research papers in international journals and conferences and has worked on projects involving IoT security, AI/ML, access-control automation, and data-driven ontology and rule generation. He is also actively involved in research coordination, faculty mentoring, student research, and entrepreneurship/startup initiatives.

Experience

12+ Years

Qualification

PhD -2025, MTech-2014, BE- 2007

Research

• Improving IoT Access Control with Context-Aware Machine Learning: Reducing Bias and Enhancing Accuracy Surendra Tyagi, Yamuna Prasad, Devesh C. Jinwala, Subhasis Bhattacharjee International Journal of Ad Hoc and Ubiquitous Computing, Vol. 49, No. 1, pp. 60–73, 2025. DOI: 10.1504/IJAHUC.2025.146121 The work investigates Context-Aware Machine Learning (CAML) for dynamically generating and adapting IoT access-control policies. The study reports accuracy improvements up to 99.9% on the smart-home dataset in the evaluated cases.
• A Fast Access Control Method in IoT Using XGB Surendra Tyagi, Yamuna Prasad, Devesh C. Jinwala, Subhasis Bhattacharjee SN Computer Science, Vol. 5, Issue 8, Article 1084, 2024. DOI: 10.1007/s42979-024-03467-z This research investigates Extreme Gradient Boosting (XGBoost) for IoT access-control decision making and compares conventional ML approaches with deep-learning approaches for access-control policy generation.
• Decentralised Ontology-Based Access Control in Internet of Things Using Social Context Surendra Tyagi, Devesh C. Jinwala, Subhasis Bhattacharjee International Journal of Ad Hoc and Ubiquitous Computing, Vol. 45, No. 4, pp. 213–225, 2024. DOI: 10.1504/IJAHUC.2024.137602 The paper proposes an ontology for decentralized, context-aware access control in IoT, using a smart-home scenario and incorporating social context into access-control decisions. The ontology was validated through simulation using Protégé.
• Automatic Creation of Ontologies and Rules from ML Models for Access Control in IoT Surendra Tyagi, Devesh C. Jinwala, Subhasis Bhattacharjee Proceedings of the 15th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2024, pp. 1–6. This work explores the automatic transformation of machine-learning model decisions into ontologies and access-control rules, connecting data-driven ML models with semantic knowledge representation for IoT security

Area of Interest

IoT Security • Context-Aware Access Control • AI/ML • Ontologies & Knowledge Representation • Smart Homes • Privacy & Security • Explainable/Automated Rule Generation • Intelligent Systems