Machine learning for intrusion detection in industrial control systems: Applications, challenges, and recommendations
Methods from machine learning are used in the design of secure Industrial Control Systems.
Such methods focus on two major areas: detection of intrusions at the network level using …
Such methods focus on two major areas: detection of intrusions at the network level using …
Correlation-based anomaly detection in industrial control systems
Industrial Control Systems (ICSs) were initially designed to be operated in an isolated
network. However, recently, ICSs have been increasingly connected to the Internet to …
network. However, recently, ICSs have been increasingly connected to the Internet to …
Can industrial intrusion detection be simple?
Cyberattacks against industrial control systems pose a serious risk to the safety of humans
and the environment. Industrial intrusion detection systems oppose this threat by …
and the environment. Industrial intrusion detection systems oppose this threat by …
A hybrid physics-based data-driven framework for anomaly detection in industrial control systems
A method referred to as PbNN is proposed to detect cyber-physical attacks through the
identification of resulting anomalies in the process dynamics of the underlying ICS. Unlike …
identification of resulting anomalies in the process dynamics of the underlying ICS. Unlike …
AI for cyberbiosecurity in water systems—A survey
Abstract The use of Artificial Intelligence (AI) is growing in areas where decisions and
consequences have high-stakes such as larger scale software, critical infrastructure, and …
consequences have high-stakes such as larger scale software, critical infrastructure, and …
AICrit: A unified framework for real-time anomaly detection in water treatment plants
Abstract Industrial Control Systems (ICS) in public infrastructure, such as water treatment
and distribution plants, have become a target of sophisticated cyber-attacks. Given the ever …
and distribution plants, have become a target of sophisticated cyber-attacks. Given the ever …
Deriving invariant checkers for critical infrastructure using axiomatic design principles
Cyber-physical systems (CPSs) in critical infrastructure face serious threats of attack,
motivating research into a wide variety of defence mechanisms such as those that monitor …
motivating research into a wide variety of defence mechanisms such as those that monitor …
Discovering a data interpreted petri net model of industrial control systems for anomaly detection
An industrial control system (ICS) can be described as an integration of heterogeneous
processes, ie, a discrete event-driven process at the automatic control layer and a …
processes, ie, a discrete event-driven process at the automatic control layer and a …
Design-knowledge in learning plant dynamics for detecting process anomalies in water treatment plants
There exist several process-based anomaly detectors for Industrial Control Systems (ICS).
Often such detectors are built using Machine learning (ML) algorithms that do not take …
Often such detectors are built using Machine learning (ML) algorithms that do not take …
Attack rules: an adversarial approach to generate attacks for Industrial Control Systems using machine learning
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 …
attack and create attacks that deceive the anomaly detection methods in Industrial Control …