Surviving False Data Injection Attacks: ...
Document type :
Communication dans un congrès avec actes
Title :
Surviving False Data Injection Attacks: An Effective Recovery Scheme for Resilient CPS
Author(s) :
Guibene, Khalil [Auteur]
Centre de Recherche en Sciences et Technologies de l'Information et de la Communication - EA 3804 [CRESTIC]
Messai, Nadhir [Auteur]
Centre de Recherche en Sciences et Technologies de l'Information et de la Communication - EA 3804 [CRESTIC]
Ayaida, Marwane [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
COMmunications NUMériques - IEMN [COMNUM - IEMN]
Centre de Recherche en Sciences et Technologies de l'Information et de la Communication - EA 3804 [CRESTIC]
Centre de Recherche en Sciences et Technologies de l'Information et de la Communication - EA 3804 [CRESTIC]
Messai, Nadhir [Auteur]
Centre de Recherche en Sciences et Technologies de l'Information et de la Communication - EA 3804 [CRESTIC]
Ayaida, Marwane [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
COMmunications NUMériques - IEMN [COMNUM - IEMN]
Centre de Recherche en Sciences et Technologies de l'Information et de la Communication - EA 3804 [CRESTIC]
Conference title :
GLOBECOM 2023 - 2023 IEEE Global Communications Conference
City :
Kuala Lumpur
Country :
Malaisie
Start date of the conference :
2023-12-04
Publisher :
IEEE
HAL domain(s) :
Physique [physics]
Sciences de l'ingénieur [physics]
Sciences de l'ingénieur [physics]
English abstract : [en]
Cyber-physical industrial systems are internet-enabled physical entities embedded with computers and control components consisting of sensors and actuators. However, inter-connecting the cyber and physical spaces led to ...
Show more >Cyber-physical industrial systems are internet-enabled physical entities embedded with computers and control components consisting of sensors and actuators. However, inter-connecting the cyber and physical spaces led to new security challenges. This paper presents a recovery controller based on a physics-informed neural network (PINN) to enhance the resilience of cyber-physical systems (CPS) against false data injection attacks (FDIA). The PINN-based controller is trained to predict corrective actions that can restore the desired operating conditions of the CPS after an attack. The proposed approach is validated on a quadruple water tank process, a benchmark system for CPS control. Results show that the PINN-based recovery controller can effectively restore the system's desired operating conditions, outperforming conventional recovery controllers that do not incorporate the physical dynamics of the CPS in their design.Show less >
Show more >Cyber-physical industrial systems are internet-enabled physical entities embedded with computers and control components consisting of sensors and actuators. However, inter-connecting the cyber and physical spaces led to new security challenges. This paper presents a recovery controller based on a physics-informed neural network (PINN) to enhance the resilience of cyber-physical systems (CPS) against false data injection attacks (FDIA). The PINN-based controller is trained to predict corrective actions that can restore the desired operating conditions of the CPS after an attack. The proposed approach is validated on a quadruple water tank process, a benchmark system for CPS control. Results show that the PINN-based recovery controller can effectively restore the system's desired operating conditions, outperforming conventional recovery controllers that do not incorporate the physical dynamics of the CPS in their design.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Source :