Time-Synchronization Attacks against Critical Infrastructures and their Mitigation

This work focuses on the security of critical infrastructures against time-synchronization attacks (TSA). A TSA can impact any network that relies on the dynamic analysis of data, by altering the time synchronization between its nodes. Such attacked networks can start failing. Some TSAs are thwarted by cyber-security tools such as authentication and confidentiality algorithms. However, such tools cannot counter TSAs that are implemented physically. Such TSAs are undetectable but they may be detected if they lead to non-plausible observations. The identification of TSAs requires in-depth knowledge of the system's operation. We focus on TSAs in two settings. First, we consider smart grids. Their control and operation require the timely knowledge of the system state, which is inferred from an estimate computed from measurements. We consider phasor measurements taken from phasor measurement units (PMUs). However, they require a precise time synchronization, which is a weakness as existing synchronization methods are vulnerable to attacks. We aim to assess the vulnerability of the synchrophasor-based state estimation of a system, by exploring the feasibility and detectability of TSAs on PMUs. A widespread technique to make the state estimation more robust is to couple it with a bad-data detection (BDD) scheme. However, it is known that false data injection attacks and TSAs can impact the state estimation without being detected by the BDD algorithms. We present practical attack strategies for undetectable TSAs and novel vulnerability conditions. One of them is a static condition that does not depend on the measurement values. We propose a security requirement that prevents it and a greedy offline algorithm that enforces it. If this requirement is satisfied, the grid may still be attacked, although we reason that it is unlikely. We identify two sufficient and necessary vulnerability conditions which depend on the measurement values. For each, we provide a metric that shows the distance between the observed and vulnerability conditions. Enforcing our requirement requires increasing the amount of measurement points of the grid. We investigate the benefits of utilizing the three-phase model instead of the direct-sequence model for security. We show that if the power system is unbalanced, then the use of the three-phase model enables to detect attacks that are undetectable if the direct-sequence model is used. Numerical results from simulations with real load profiles from the Lausanne grid, confirm our findings. Second, we consider sensor networks for passive-source localization. We focus on the localization of a passive source from time difference of arrival (TDOA) measurements. Such measurements are highly sensitive to time-synchronization offsets. We first illustrate that TSAs can affect the localization and we show that residual analysis does not enable the detection and identification of TSAs. Second, we propose a two-step TDOA-localization technique that is robust against TSAs. It uses a known source to define a weight for each pair of sensors, reflecting the confidence in their synchronization. We then use the weighted least-squares estimator with the new weights and the TDOA measurements received from the unknown source. Our method either identifies the network as being too corrupt, or gives a corrected estimate of the unknown position along with a confidence metric. Numerical results illustrate the performance of our technique