Think Smart, Play Dumb: Analyzing Deception in Hardware Trojan Detection Using Game Theory. - Tapadhir Das; Abdel Rahman Eldosouky; Shamik Sengupta (Cyber Security, 2020)

Friend or Foe: Discerning Benign vs Malicious Software and Malware Family. - Aaron Walker; Tapadhir Das; Raj Mani Shukla; Shamik Sengupta (GLOBECOM, 2021)

Sharing is Caring: Optimized Threat Visualization for a Cybersecurity Data Sharing Platform. - Adam Cassell; Tapadhir Das; Zachary Black; Farhan Sadique; James Schnebly; Sergiu Dascalu; Shamik Sengupta; Jeff Springer (NCA, 2021)

The Devil is in the Details: Confident & Explainable Anomaly Detector for Software-Defined Networks. - Tapadhir Das; Raj Mani Shukla; Shamik Sengupta (NCA, 2021)

Casting a Wide Net: An Internet of Things Testbed for Cybersecurity Education and Research. - Jay Thom; Tapadhir Das; Bibek Shrestha; Shamik Sengupta; Engin Arslan (SPECTS, 2021)

Imposters Among Us: A Supervised Learning Approach to Anomaly Detection in IoT Sensor Data. - Tapadhir Das; Raj Mani Shukla; Shamik Sengupta (WF-IoT, 2021)

Ohana Means Family: Malware Family Classification using Extreme Learning Machines. - Aaron Walker; Raj Mani Shukla; Tapadhir Das; Shamik Sengupta (CCNC, 2022)

Flood Control: TCP-SYN Flood Detection for Software-Defined Networks using OpenFlow Port Statistics. - Tapadhir Das; Osama Abu Hamdan; Shamik Sengupta; Engin Arslan (CSR, 2022)

Finding the Sweet Spot for Data Anonymization: A Mechanism Design Perspective. - AbdelRahman Eldosouky; Tapadhir Das; Anuraag Kotra; Shamik Sengupta (IEEE Access, 2022)

UNR-IDD: Intrusion Detection Dataset using Network Port Statistics. - Tapadhir Das; Osama Abu Hamdan; Raj Mani Shukla; Shamik Sengupta; Engin Arslan (CCNC, 2023)

Eyes on the Road: A Survey on Cyber Attacks and Defense Solutions for Vehicular Ad-Hoc Networks. - Amber Hankins; Tapadhir Das; Shamik Sengupta; David Feil-Seifer (CCWC, 2023)

Less is More: Deep Learning Framework for Digital Forensics in Resource-Constrained Environments. - Suman Rath; Tapadhir Das; Ignacio Astaburuaga; Shamik Sengupta (ISDFS, 2023)

Runs in the Family: Malware Family Variants Identification through API Sequence and Frequency Analysis. - Aaron Walker; Raj Mani Shukla; Tapadhir Das; Shamik Sengupta (MCNA, 2023)

Give and Take: Federated Transfer Learning for Industrial IoT Network Intrusion Detection. - Lochana Telugu Rajesh; Tapadhir Das; Raj Mani Shukla; Shamik Sengupta (TrustCom, 2023)

What Could Possibly Go Wrong? Identification of Current Challenges and Prospective Opportunities for Anomaly Detection in Internet of Things. - Tapadhir Das; Raj Mani Shukla; Shamik Sengupta (IEEE Netw., 2023)

Modeling the Abnormality: Machine Learning-based Anomaly and Intrusion Detection in Software-defined Networks. - Tapadhir Das (2023)

Telling Apart: ML Framework Towards Cyber Attack and Fault Differentiation in Microgrids. - Tapadhir Das; Suman Rath; Shamik Sengupta (ICPS, 2024)

Evaluation of Ensemble Learning for Mitigating Adversarial Attacks in Industrial Object Detection. - Shashank Pulijala; Sara Shahin; Tapadhir Das; Raj Mani Shukla (IECON, 2024)

Decentralized Privacy-Preserving Federated Learning for Ultrasonic Nerve Image Segmentation. - Gowtham Vinjamuri; Suvendu Chandan Nayak; Rekha Sahu; Raj Mani Shukla; Tapadhir Das (IECON, 2024)

Improvise, Adapt, Overcome: Dynamic Resiliency Against Unknown Attack Vectors in Microgrid Cybersecurity Games. - Suman Rath; Tapadhir Das; Shamik Sengupta (IEEE Trans. Smart Grid, 2024)

GCAP: Cyber Attack Progression Framework for Smart Grid Infrastructures. - Tapadhir Das; Suman Rath; Shamik Sengupta (IEEE Internet Things J., 2025)

Bringing to Light: Adversarial Poisoning Detection for ML-Based IDS in Software-Defined Networks. - Tapadhir Das; Raj Mani Shukla; Suman Rath; Shamik Sengupta (IEEE Trans. Netw. Sci. Eng., 2025)

Poisoning the Well: Adversarial Poisoning on ML-Based Software-Defined Network Intrusion Detection Systems. - Tapadhir Das; Raj Mani Shukla; Shamik Sengupta (IEEE Trans. Netw. Sci. Eng., 2025)