| Title | Hardware-Trojan Classification based on the Structure of Trigger Circuits Utilizing Random Forests |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Kurihara, Tatsuki, Togawa, Nozomu |
| Conference Name | 2021 IEEE 27th International Symposium on On-Line Testing and Robust System Design (IOLTS) |
| Keywords | Benchmark testing, composability, feature extraction, Hardware, hardware security, hardware trojan, integrated circuits, Internet of Things, machine learning, Manufacturing, netlist, pubcrawl, Random Forest, resilience, Resiliency, trojan horse detection, Trojan horses |
| Abstract | Recently, with the spread of Internet of Things (IoT) devices, embedded hardware devices have been used in a variety of everyday electrical items. Due to the increased demand for embedded hardware devices, some of the IC design and manufacturing steps have been outsourced to third-party vendors. Since malicious third-party vendors may insert malicious circuits, called hardware Trojans, into their products, developing an effective hardware Trojan detection method is strongly required. In this paper, we propose 25 hardware-Trojan features based on the structure of trigger circuits for machine-learning-based hardware Trojan detection. Combining the proposed features into 11 existing hardware-Trojan features, we totally utilize 36 hardware-Trojan features for classification. Then we classify the nets in an unknown netlist into a set of normal nets and Trojan nets based on the random-forest classifier. The experimental results demonstrate that the average true positive rate (TPR) becomes 63.6% and the average true negative rate (TNR) becomes 100.0%. They improve the average TPR by 14.7 points while keeping the average TNR compared to existing state-of-the-art methods. In particular, the proposed method successfully finds out Trojan nets in several benchmark circuits, which are not found by the existing method. |
| DOI | 10.1109/IOLTS52814.2021.9486700 |
| Citation Key | kurihara_hardware-trojan_2021 |
Hardware-Trojan Classification based on the Structure of Trigger Circuits Utilizing Random Forests