In-Depth Feature Selection for the Statistical Machine Learning-Based Botnet Detection in IoT Networks. - Rajesh Kalakoti; Sven Nõmm; Hayretdin Bahsi (IEEE Access, 2022)

Improving Transparency and Explainability of Deep Learning Based IoT Botnet Detection Using Explainable Artificial Intelligence (XAI). - Rajesh Kalakoti; Sven Nõmm; Hayretdin Bahsi (ICMLA, 2023)

Enhancing IoT Botnet Attack Detection in SOCs with an Explainable Active Learning Framework. - Rajesh Kalakoti; Sven Nõmm; Hayretdin Bahsi (AIIoT, 2024)

Explainable Federated Learning for Botnet Detection in IoT Networks. - Rajesh Kalakoti; Hayretdin Bahsi; Sven Nõmm (CSR, 2024)

Explainable Transformer-based Intrusion Detection in Internet of Medical Things (IoMT) Networks. - Rajesh Kalakoti; Sven Nõmm; Hayretdin Bahsi (ICMLA, 2024)

Improving IoT Security With Explainable AI: Quantitative Evaluation of Explainability for IoT Botnet Detection. - Rajesh Kalakoti; Hayretdin Bahsi; Sven Nõmm (IEEE Internet Things J., 2024)

Evaluating Explainable AI for Deep Learning-Based Network Intrusion Detection System Alert Classification. - Rajesh Kalakoti; Risto Vaarandi; Hayretdin Bahsi; Sven Nõmm (ICISSP (1), 2025)

Comprehensive Feature Selection for Machine Learning-Based Intrusion Detection in Healthcare IoMT Networks. - Muaan ur Rehman; Rajesh Kalakoti; Hayretdin Bahsi (ICISSP (2), 2025)

Federated Learning of Explainable AI(FedXAI) for deep learning-based intrusion detection in IoT networks. - Rajesh Kalakoti; Sven Nõmm; Hayretdin Bahsi (Comput. Networks, 2025)