Concurrent hardware Trojan detection in wireless cryptographic ICs

We introduce a Concurrent Hardware Trojan Detection (CHTD) methodology for wireless cryptographic integrated circuits (ICs), based on continuous extraction of a side-channel fingerprint and evaluation by a trained on-chip neural classifier. While similar statistical side-channel fingerprinting methods have been extensively studied in the past, they operate either before an IC is deployed or, periodically, during idle times, after an IC is deployed. Therefore, they can be easily evaded by a hardware Trojan which remains dormant at all times except during normal operation. In contrast, the proposed methodology operates concurrently with the normal functionality of the IC and is, therefore, much harder to evade. The proposed methodology is demonstrated using a hybrid experimentation platform consisting of (i) a custom-designed wireless cryptographic IC, infested with hardware Trojans that are controllable to be either active or dormant, (ii) a Spice-level simulation model of the fingerprint extraction circuit, and (iii) a custom-designed programmable analog neural network IC. Experimental results corroborate that the proposed CHTD methodology effectively identifies hardware Trojans when they are active, while not incurring any false positives when they are absent or dormant.