Improving DDoS Attack Detection Leveraging a Multi-aspect Ensemble Feature Selection. - Pegah Golchin; Ralf Kundel; Tim Steuer; Rhaban Hark; Ralf Steinmetz (NOMS, 2022)

CML-IDS: Enhancing Intrusion Detection in SDN Through Collaborative Machine Learning. - Pegah Golchin; Chengbo Zhou; Pratyush Agnihotri; Mehrdad Hajizadeh; Ralf Kundel; Ralf Steinmetz (CNSM, 2023)

FSA-IDS: A Flow-based Self-Active Intrusion Detection System. - Mehrdad Hajizadeh; Sudip Barua; Pegah Golchin (NOMS, 2023)

SSCL-IDS: Enhancing Generalization of Intrusion Detection with Self-Supervised Contrastive Learning. - Pegah Golchin; Nima Rafiee; Mehrdad Hajizadeh; Ahmad Khalil 002; Ralf Kundel; Ralf Steinmetz (IFIP Networking, 2024)

A Data-Driven Solution for Improving Transferability of Traffic Flow Feature Selection. - Pegah Golchin; Nima Rafiee; Ralf Kundel (IFIP Networking, 2024)

Integrating Online Learning with Collaborative Machine Learning for Continuous Intrusion Detection in SDN. - Pegah Golchin; Chengbo Zhou; Hengyu Liu; Björn Scheuermann 001; Ralf Kundel; Tobias Meuser (NFV-SDN, 2024)

Federated Learning with Heterogeneous Data Handling for Robust Vehicular Object Detection. - Ahmad Khalil 002; Tizian Dege; Pegah Golchin; Rostyslav Olshevskyi; Antonio Fernández Anta; Tobias Meuser (CoRR, 2024)

Machine Learning Models in Network Intrusion Detection Systems: Self-Supervised Detection of Malicious Flows and Traffic Patterns Recognition in Programmable Networks. - Pegah Golchin (2024)

DeepRed: A Deep Learning-Powered Command and Control Framework for Multi-Stage Red Teaming Against ML-based Network Intrusion Detection Systems. - Mehrdad Hajizadeh; Pegah Golchin; Ehsan Nowroozi; Maria Rigaki; Veronica Valeros; Sebastián García; Mauro Conti; Thomas Bauschert (WOOT, 2025)