TY - JOUR
T1 - Sequential false data injection cyberattacks in water distribution systems targeting storage tanks; a bi-level optimization model
AU - Moazeni, Faegheh
AU - Khazaei, Javad
N1 - Funding Information:
This research was under support from Penn State’s center for security research and education (CSRE), USA under 2020 Homeland Security Seed Grant.
Funding Information:
This research was under support from Penn State's center for security research and education (CSRE), USA under 2020 Homeland Security Seed Grant.
Publisher Copyright:
© 2021
PY - 2021/7
Y1 - 2021/7
N2 - While digital interconnectivity of smart cities has significantly enhanced the quality of life of residents, it has introduced cybersecurity challenges that may interrupt the operation of critical infrastructures. Water distribution systems are among the most critical infrastructures in smart cities that need to be secured against potential cyberattacks. False data injection cyberattacks in water distribution systems can be designed to bypass bad data detection algorithms, generating false measurements that ultimately lead to cascading failures. Developing models for these cyberattacks and analyzing them will elucidate hidden layers and tactics used to design the attacks, helping water systems’ authorities to improve and upgrade state-estimation processes and detection algorithms accordingly. In this paper, a bi-level nonlinear optimization cyberattack model is proposed that will result in sequential tank's overflow or fully withdrawn in less than three hours. The attack model is developed based upon injecting false data into the hourly measurements of the pump(s) feeding the tank, as well as the total demand of the network. By modifying a few estimation parameters in the neighborhood of the targeted tank, these false data injections are deliberately designed to bypass the existing water system's state-estimation and bad data detection methods.
AB - While digital interconnectivity of smart cities has significantly enhanced the quality of life of residents, it has introduced cybersecurity challenges that may interrupt the operation of critical infrastructures. Water distribution systems are among the most critical infrastructures in smart cities that need to be secured against potential cyberattacks. False data injection cyberattacks in water distribution systems can be designed to bypass bad data detection algorithms, generating false measurements that ultimately lead to cascading failures. Developing models for these cyberattacks and analyzing them will elucidate hidden layers and tactics used to design the attacks, helping water systems’ authorities to improve and upgrade state-estimation processes and detection algorithms accordingly. In this paper, a bi-level nonlinear optimization cyberattack model is proposed that will result in sequential tank's overflow or fully withdrawn in less than three hours. The attack model is developed based upon injecting false data into the hourly measurements of the pump(s) feeding the tank, as well as the total demand of the network. By modifying a few estimation parameters in the neighborhood of the targeted tank, these false data injections are deliberately designed to bypass the existing water system's state-estimation and bad data detection methods.
UR - http://www.scopus.com/inward/record.url?scp=85103791247&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85103791247&partnerID=8YFLogxK
U2 - 10.1016/j.scs.2021.102895
DO - 10.1016/j.scs.2021.102895
M3 - Article
AN - SCOPUS:85103791247
VL - 70
JO - Sustainable Cities and Society
JF - Sustainable Cities and Society
SN - 2210-6707
M1 - 102895
ER -