INTRUSION RESPONSE FOR CYBER-PHYSICAL SYSTEMS: A MODEL-FREE DEEP REINFORCEMENT LEARNING APPROACH
MAYSM BASHENDY - 2022 - qspace.qu.edu.qa
Cyberattacks on Cyber-Physical Systems (CPSs) are on the rise due to CPS increased
networked connectivity, which may cause costly environmental hazards as well as human …
networked connectivity, which may cause costly environmental hazards as well as human …
Autonomous Response Agent for Cyber Physical System Attacks: A Model-Free Deep Reinforcement Learning Approach (Drl-Irs)
Cyber physical systems are increasingly targeted by cyber-attacks that pose significant risks,
including human and financial losses, as well as environmental damage. Autonomous …
including human and financial losses, as well as environmental damage. Autonomous …
A performance evaluation of deep reinforcement learning for model-based intrusion response
S Iannucci, OD Barba, V Cardellini… - 2019 ieee 4th …, 2019 - ieeexplore.ieee.org
Given the always increasing size of computer systems, manually protecting them in case of
attacks is infeasible and error-prone. For this reason, several Intrusion Response Systems …
attacks is infeasible and error-prone. For this reason, several Intrusion Response Systems …
Comparison and investigation of AI-based approaches for cyberattack detection in cyber-physical systems
The demand for cyber-physical systems (CPSs) has recently increased in various domains,
such as smart grids, intelligent transportation, and critical infrastructure. The massive data …
such as smart grids, intelligent transportation, and critical infrastructure. The massive data …
An intrusion response approach for elastic applications based on reinforcement learning
S Iannucci, E Casalicchio… - 2021 IEEE Symposium …, 2021 - ieeexplore.ieee.org
Intrusion Response is a relatively new field of research. Several model-based techniques
have been proposed that range from static mapping to complex stateful approaches …
have been proposed that range from static mapping to complex stateful approaches …
Interpretable Cross-Layer Intrusion Response System Based on Deep Reinforcement Learning for Industrial Control Systems
H Chen, Y Lai, J Liu, H Wanyan - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Owing to the increasing number of cybersecurity threats targeting industrial control systems
(ICSs), intrusion response systems (IRSs) have become essential. However, the current …
(ICSs), intrusion response systems (IRSs) have become essential. However, the current …
Intrusion response systems for cyber-physical systems: A comprehensive survey
Abstract Cyberattacks on Cyber-Physical Systems (CPS) are on the rise due to CPS
increased networked connectivity and may cause costly environmental hazards as well as …
increased networked connectivity and may cause costly environmental hazards as well as …
[HTML][HTML] Employing Deep Reinforcement Learning to Cyber-Attack Simulation for Enhancing Cybersecurity
In the current landscape where cybersecurity threats are escalating in complexity and
frequency, traditional defense mechanisms like rule-based firewalls and signature-based …
frequency, traditional defense mechanisms like rule-based firewalls and signature-based …
Stealthy False Data Injection Attacks Detection and Classification in Cyber-Physical Systems Using Deep Reinforcement Learning
L Xin, G He, Z Long - IEEE Transactions on Automation Science …, 2024 - ieeexplore.ieee.org
Cyber-physical systems (CPSs) are increasingly threatened by stealthy false data injection
(SFDI) attacks, which compromise system integrity by manipulating control signals and …
(SFDI) attacks, which compromise system integrity by manipulating control signals and …
Real-time cyber-physical security solution leveraging an integrated learning-based approach
Cyber-Physical Systems (CPS) has emerged as a paradigm that connects cyber and
physical worlds, which provides unprecedented opportunities to realize intelligent …
physical worlds, which provides unprecedented opportunities to realize intelligent …