SecureSIS: Securing SIS Safety Functions With Safety Attributes and BPCS Information

In high-stakes process industries, the Basic Process Control System (BPCS) relies on conventional control to enhance productivity, while the Safety Instrumented System (SIS) uses safety functions to maintain safety. Compared to the BPCS, attackers targeting the SIS can modify safety function activation conditions to trigger them prematurely or to evade the activation of the safety function. While various attack detection methods focus on the BPCS, they often overlook the SIS. This can lead to undetected safety breaches, significantly increasing the risk of catastrophic fault. Recent methods face three key limitations that hinder their practical application to SIS. First, both attackers and engineers can exploit the hot update mechanism of SIS to add or modify control logic. However, current methods lack verification for the newly added or modified logic. Second, current methods are unable to assess the rationality of dangerous value ranges. Third, these methods struggle to distinguish between faults and attacks, making it difficult to determine the appropriate time to activate the SIS’s safety function. To overcome these limitations, we propose SecureSIS, a method for securing SIS safety functions by leveraging the safety attributes of the SIS and incorporating information from the BPCS. The core of SecureSIS includes: 1) using the safety attributes of the SIS to verify automatically extracted candidate control logic detection rules; 2) utilizing information from the BPCS to verify automatically extracted candidate value range detection rules; and 3) distinguishing between safety function attacks and industrial process faults with validated rules and integration of process data from BPCS. Our scheme was evaluated using a Tricon SIS controller deployed on a gas pipeline network platform. The results indicate that SecureSIS achieved 97.3% accuracy in detecting data injection attacks and a detection accuracy of 96.0% for control logic modification attacks. Compared with the other representative detection approaches, our scheme has better detection performance.