Flip-Lock: A Flip-Flop-Based Logic Locking Technique for Thwarting ML-based and Algorithmic Structural Attacks

Machine learning (ML) and algorithmic structural attacks have highlighted the possibility of utilizing structural leakages of an obfuscated circuit to reverse engineer the locking mechanism. These structural leakages are rooted in security-agnostic synthesis tools that lead to discernible patterns within the vicinity of the locking substructures. This paper has two contributions. Firstly, we present the innovative Flip-lock, a novel approach that utilizes flip-flops along logic gates to prevent synthesis tools' structural leakages. As this is the first work that incorporates flip-flops in locking structures, our second contribution is the development of a comprehensive analysis tool designed to identify and assess potential structural leakages in the vicinity of flip-flops within circuits. We name our tool Flip-attack. We employ the Flip-attack analysis to strengthen Flip-lock's resilience against potential future attacks. Our findings demonstrate that Flip-lock possesses the capability to neutralize all existing state-of-the-art structural attacks effectively. Furthermore, by enhancing Flip-lock through the incorporation of our analysis tool, we establish a robust defense mechanism that can safeguard the circuit's security against potential future threats.