Sequential false data injection cyberattacks in water distribution systems targeting storage tanks; a bi-level optimization model

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a bi-level nonlinear optimization cyberattack model is proposed that will result in sequential tank's overflow or fully withdrawn in less than three hours.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.