Tapadhir Das
Orcid: 0000-0002-4793-8982
According to our database1,
Tapadhir Das
authored at least 17 papers
between 2020 and 2024.
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Bibliography
2024
Improvise, Adapt, Overcome: Dynamic Resiliency Against Unknown Attack Vectors in Microgrid Cybersecurity Games.
IEEE Trans. Smart Grid, July, 2024
2023
Modeling the Abnormality: Machine Learning-based Anomaly and Intrusion Detection in Software-defined Networks.
PhD thesis, 2023
What Could Possibly Go Wrong? Identification of Current Challenges and Prospective Opportunities for Anomaly Detection in Internet of Things.
IEEE Netw., 2023
Give and Take: Federated Transfer Learning for Industrial IoT Network Intrusion Detection.
Proceedings of the 22nd IEEE International Conference on Trust, 2023
Runs in the Family: Malware Family Variants Identification through API Sequence and Frequency Analysis.
Proceedings of the International Conference on Multimedia Computing, 2023
Less is More: Deep Learning Framework for Digital Forensics in Resource-Constrained Environments.
Proceedings of the 11th International Symposium on Digital Forensics and Security, 2023
Eyes on the Road: A Survey on Cyber Attacks and Defense Solutions for Vehicular Ad-Hoc Networks.
Proceedings of the 13th IEEE Annual Computing and Communication Workshop and Conference, 2023
Proceedings of the 20th IEEE Consumer Communications & Networking Conference, 2023
2022
IEEE Access, 2022
Flood Control: TCP-SYN Flood Detection for Software-Defined Networks using OpenFlow Port Statistics.
Proceedings of the IEEE International Conference on Cyber Security and Resilience, 2022
Proceedings of the 19th IEEE Annual Consumer Communications & Networking Conference, 2022
2021
Imposters Among Us: A Supervised Learning Approach to Anomaly Detection in IoT Sensor Data.
Proceedings of the 7th IEEE World Forum on Internet of Things, 2021
Casting a Wide Net: An Internet of Things Testbed for Cybersecurity Education and Research.
Proceedings of the 2021 International Symposium on Performance Evaluation of Computer and Telecommunication Systems, 2021
The Devil is in the Details: Confident & Explainable Anomaly Detector for Software-Defined Networks.
Proceedings of the 20th IEEE International Symposium on Network Computing and Applications, 2021
Sharing is Caring: Optimized Threat Visualization for a Cybersecurity Data Sharing Platform.
Proceedings of the 20th IEEE International Symposium on Network Computing and Applications, 2021
Proceedings of the IEEE Global Communications Conference, 2021
2020
Think Smart, Play Dumb: Analyzing Deception in Hardware Trojan Detection Using Game Theory.
Proceedings of the 2020 International Conference on Cyber Security and Protection of Digital Services, 2020