SiPGuard: Run-Time System-in-Package Security Monitoring via Power Noise Variation

Abstract

As Moore’s law comes to a crawl, advanced package and integration techniques become increasingly crucial by allowing for the combination of fabricated silicon dies, so-called chiplet, to constitute system-in-package (SiP) achieving a much better yield and time-to-market. However, due to inherent security concerns within the convoluted semiconductor supply chain and in-field environment, hostile attacks targeting software and hardware applications can present a formidable challenge to ensuring the security of SiP. Even worse, the immanent black-box nature of product chiplets renders most conventional security inspection and testing solutions less useful. Therefore, we present our SiPGuard in this article to enable the security monitoring capability during run time to noninvasively track the application-level behaviors of target chiplets and detect any deviations potentially induced by underlying malicious intrusions. The security monitoring mechanism utilizes information-bearing system-level power noise variation and machine learning (ML) techniques. Specifically, we utilize a trusted field-programmable gate array (FPGA) chiplet as our trust anchor to implement the lightweight power sensor and on-chip ML inference engine for near-sensor analysis. We prototype our solution on a 2.5-D chiplet-based FPGA device and demonstrate the effectiveness against threats at software/hardware levels by identifying the consequent power anomalies of malicious activities.