162 citations · 174 across the 6 of their papers we have counts for
6 papers
A Cyber-Twin Based Honeypot for Gathering Threat Intelligence
Muhammad Azmi Umer, Zhan Xuna, Yan Lin Aung +2
Critical Infrastructure (CI) is prone to cyberattacks. Several techniques have been developed to protect CI against such attacks. In this work, we describe a honeypot based on a cy…
Attack Pattern Mining to Discover Hidden Threats to Industrial Control Systems
Muhammad Azmi Umer, Chuadhry Mujeeb Ahmed, Aditya Mathur +1
This work focuses on validation of attack pattern mining in the context of Industrial Control System (ICS) security. A comprehensive security assessment of an ICS requires generati…
Adversarial Sample Generation for Anomaly Detection in Industrial Control Systems
Abdul Mustafa, Muhammad Talha Khan, Muhammad Azmi Umer +2
Machine learning (ML)-based intrusion detection systems (IDS) are vulnerable to adversarial attacks. It is crucial for an IDS to learn to recognize adversarial examples before mali…
Machine Learning for Intrusion Detection in Industrial Control Systems: Applications, Challenges, and Recommendations
Muhammad Azmi Umer, Khurum Nazir Junejo, Muhammad Taha Jilani +1
Methods from machine learning are being applied to design Industrial Control Systems resilient to cyber-attacks. Such methods focus on two major areas: the detection of intrusions…
A Data-Centric Approach to Generate Invariants for a Smart Grid Using Machine Learning
Danish Hudani, Muhammad Haseeb, Muhammad Taufiq +2
Cyber-Physical Systems (CPS) have gained popularity due to the increased requirements on their uninterrupted connectivity and process automation. Due to their connectivity over the…
Attack Rules: An Adversarial Approach to Generate Attacks for Industrial Control Systems using Machine Learning
Muhammad Azmi Umer, Chuadhry Mujeeb Ahmed, Muhammad Taha Jilani +1
Adversarial learning is used to test the robustness of machine learning algorithms under attack and create attacks that deceive the anomaly detection methods in Industrial Control…