Integrating Design and Data Centric Approaches to Generate Invariants for Distributed Attack Detection. - Muhammad Azmi Umer; Aditya Mathur; Khurum Nazir Junejo; Sridhar Adepu (CPS-SPC@CCS, 2017)

Generating invariants using design and data-centric approaches for distributed attack detection. - Muhammad Azmi Umer; Aditya Mathur; Khurum Nazir Junejo; Sridhar Adepu (Int. J. Crit. Infrastructure Prot., 2020)

Attack Rules: An Adversarial Approach to Generate Attacks for Industrial Control Systems using Machine Learning. - Muhammad Azmi Umer; Chuadhry Mujeeb Ahmed; Muhammad Taha Jilani; Aditya P. Mathur (CPSIOTSEC@CCS, 2021)

A Data-Centric Approach to Generate Invariants for a Smart Grid Using Machine Learning. - Danish Hudani; Muhammad Haseeb; Muhammad Taufiq; Muhammad Azmi Umer; Nandha Kumar Kandasamy (SAT-CPS@CODASPY, 2022)

Effect of time patterns in mining process invariants for industrial control systems: an experimental study. - Muhammad Azmi Umer; Aditya Mathur; Muhammad Taha Jilani (SEA4DQ@ESEC/SIGSOFT FSE, 2022)

Machine learning for intrusion detection in industrial control systems: Applications, challenges, and recommendations. - Muhammad Azmi Umer; Khurum Nazir Junejo; Muhammad Taha Jilani; Aditya P. Mathur (Int. J. Crit. Infrastructure Prot., 2022)

Generated and Validated Invariants of EPIC Smart Grid. - Danish Hudani; Muhammad Haseeb; Muhammad Taufiq; Muhammad Azmi Umer; Nandha Kumar Kandasamy (IEEE DataPort, 2022)

Decision tree based invariants for intrusion detection in industrial control system. - Abdul Samiah; Muhammad Azmi Umer; Shama Siddiqui (Comput. Secur., 2025)

Adversarial Sample Generation for Anomaly Detection in Industrial Control Systems. - Abdul Mustafa; Muhammad Talha Khan; Muhammad Azmi Umer; Zaki Masood; Chuadhry Mujeeb Ahmed (CoRR, 2025)