Publications Details

Detecting Stealthy False Data Injection Attacks in State of Charge Estimation Using Sensor Encoding

Trevizan, Rodrigo D.; Brien, Vittal S.'.; Rao, Vittal S.

This paper introduces a method for detecting stealthy false data injection attacks on the sensors of state of charge estimation algorithms used in battery management systems (BMSs). This method is based on sensor encoding, which is the active modification of sensor data streams. This method implements low-cost verification of the integrity of measurement data, allowing for the detection of stealthy additive attack vectors. It is considered that these attacks are crafted by malicious actors with knowledge of system models and who are capable of tampering with any number of measurements. The solution involves encoding all vulnerable measurements. The effectiveness of the method is demonstrated by simulations, where a stealthy attack on an encoded measurement vector captured by a BMS generates large residuals that trigger a chi-squared anomaly detector. Within the context of a defense-in-depth strategy, this method can be combined with other cybersecurity controls, such as encryption of data-in-transit, to equip cyberphysical systems with an additional line of defense against cyberattacks.