Framework of Hardware Trojan Detection Leveraging Structural Checking Tool

Since there is a significant demand for obtaining third-party soft Intellectual Property (IP) by first-party integrated circuit (IC) vendors, it is becoming easier for adversaries to insert malicious logic known as hardware Trojans into designs. Due to this, vendors need to find ways to screen the third-party IPs for possible security threats and then mitigate them. The development of the Structural Checking (SC) tool provides a solution to this issue. This tool analyzes the structure of an unknown soft IP design and creates a network of all the signals within the design and how they are connected to each other. In addition, these signals will be assigned with assets. Assets describe the central role of a signal in the entire design. These assets are then used to create asset patterns, which will be crucial for this thesis research. Previous research on SC tool focuses on Trojan detection by comparing and matching an unknown design to a trusted design in a Golden Reference Library. In this thesis research, another method of Trojan detection has been implemented in the SC tool, which focuses on recognizing specific asset patterns that mainly exist in Trojan-infested designs. These specific asset patterns can then be used to check against unknown designs for Trojans without using a Golden Reference Library. This thesis improves this method by creating a new framework for easily identifying the unique Trojan asset patterns

Trojan Detection Expansion of Structural Checking

With the growth of the integrated circuit (IC) market, there has also been a rise in demand for third-party soft intellectual properties (IPs). However, the growing use of such Ips makes it easier for adversaries to hide malicious code, like hardware Trojans, into these designs. Unlike software Trojan detection, hardware Trojan detection is still an active research area. One proposed approach to this problem is the Structural Checking tool, which can detect hardware Trojans using two methodologies. The first method is a matching process, which takes an unknown design and attempts to determine if it might contain a Trojan by matching the unknown design to designs in a Golden Reference Library (GRL). The other method is interpreting structural elements of specific Trojan taxonomies via the use of Trojan detection functions, which is what this thesis research expands upon. The objective of this research is to enhance the tool’s capabilities by incorporating three additional Trojan taxonomies into the list of detectable Trojans through the implementation of new Trojan detection functions. This expansion to the Structural Checking tool is achieved through the study of sensitive data leakage Trojans, data modification Trojans, and denial-of-service Trojans