NSPG: Natural language Processing-based Security Property Generator for Hardware Security Assurance

The efficiency of validating complex System-on-Chips (SoCs) is contingent on the quality of the security properties provided. Generating security properties with traditional approaches often requires expert intervention and is limited to a few IPs, thereby resulting in a time-consuming and non-robust process. To address this issue, we, for the first time, propose a novel and automated Natural Language Processing (NLP)-based Security Property Generator (NSPG). Specifically, our approach utilizes hardware documentation in order to propose the first hardware security-specific language model, HS-BERT, for extracting security properties dedicated to hardware design. It is capable of phasing a significant amount of hardware specification, and the generated security properties can be easily converted into hardware assertions, thereby reducing the manual effort required for hardware verification. NSPG is trained using sentences from several SoC documentations and achieves up to 88% accuracy for property classification, outperforming ChatGPT. When assessed on five untrained OpenTitan hardware IP documents, NSPG aided in identifying eight security vulnerabilities in the buggy OpenTitan SoC presented in Hack@DAC 2022.