Anomaly Detection in Industrial Networks using Machine Learning: A Roadmap. - Ankush Meshram; Christian Haas 003 (ML4CPS, 2016)

Towards Computer-Aided Security Life Cycle Management for Critical Industrial Control Systems. - Florian Patzer; Ankush Meshram; Pascal Birnstill; Christian Haas 003; Jürgen Beyerer (CRITIS, 2018)

Context-Aware Software-Defined Networking for Automated Incident Response in Industrial Networks. - Florian Patzer; Philipp Lüdtke; Ankush Meshram; Jürgen Beyerer (ICISSP (Revised Selected Papers), 2019)

Automated Incident Response for Industrial Control Systems Leveraging Software-defined Networking. - Florian Patzer; Ankush Meshram; Maximilian Heß (ICISSP, 2019)

CrossTest: a cross-domain physical testbed environment for cybersecurity performance evaluations. - Markus Karch; Dennis Rösch; André Kummerow; Ankush Meshram; Christian Haas 003; Steffen Nicolai (ETFA, 2022)

Towards a Better Understanding of Machine Learning based Network Intrusion Detection Systems in Industrial Networks. - Anne Borcherding; Lukas Feldmann; Markus Karch; Ankush Meshram; Jürgen Beyerer (ICISSP, 2022)

POET: A Self-learning Framework for PROFINET Industrial Operations Behaviour. - Ankush Meshram; Markus Karch; Christian Haas 003; Jürgen Beyerer (TRIDENTCOM, 2022)

Self-learning Anomaly Detection in Industrial Production - Ankush Meshram (2022)

Towards Self-learning Industrial Process Behaviour from Payload Bytes for Anomaly Detection. - Ankush Meshram; Markus Karch; Christian Haas 003; Jürgen Beyerer (ETFA, 2023)

Protocol-Agnostic Detection of Stealth Attacks on Networked Control Systems. - Hauke Heseding; Moritz Dieing; Ankush Meshram; Martina Zitterbart (INDIN, 2023)