Jean-Pierre Seifert

h-index12
2papers
422citations

2 Papers

3.8CRJul 21, 2021
Trojan Awakener: Detecting Dormant Malicious Hardware Using Laser Logic State Imaging (Extended Version)

Thilo Krachenfels, Jean-Pierre Seifert, Shahin Tajik

The threat of hardware Trojans (HTs) and their detection is a widely studied field. While the effort for inserting a Trojan into an application-specific integrated circuit (ASIC) can be considered relatively high, especially when trusting the chip manufacturer, programmable hardware is vulnerable to Trojan insertion even after the product has been shipped or during usage. At the same time, detecting dormant HTs with small or zero-overhead triggers and payloads on these platforms is still a challenging task, as the Trojan might not get activated during the chip verification using logical testing or physical measurements. In this work, we present a novel Trojan detection approach based on a technique known from integrated circuit (IC) failure analysis, capable of detecting virtually all classes of dormant Trojans. Using laser logic state imaging (LLSI), we show how supply voltage modulations can awaken inactive Trojans, making them detectable using laser voltage imaging techniques. Therefore, our technique does not require triggering the Trojan. To support our claims, we present three case studies on 28 and 20 SRAM- and flash-based field-programmable gate arrays (FPGAs). We demonstrate how to detect with high confidence small changes in sequential and combinatorial logic as well as in the routing configuration of FPGAs in a non-invasive manner. Finally, we discuss the practical applicability of our approach on dormant analog Trojans in ASICs.

13.6CRFeb 23, 2021
Automatic Extraction of Secrets from the Transistor Jungle using Laser-Assisted Side-Channel Attacks

Thilo Krachenfels, Tuba Kiyan, Shahin Tajik et al.

The security of modern electronic devices relies on secret keys stored on secure hardware modules as the root-of-trust (RoT). Extracting those keys would break the security of the entire system. As shown before, sophisticated side-channel analysis (SCA) attacks, using chip failure analysis (FA) techniques, can extract data from on-chip memory cells. However, since the chip's layout is unknown to the adversary in practice, secret key localization and reverse engineering are onerous tasks. Consequently, hardware vendors commonly believe that the ever-growing physical complexity of the integrated circuit (IC) designs can be a natural barrier against potential adversaries. In this work, we present a novel approach that can extract the secret key without any knowledge of the IC's layout, and independent from the employed memory technology as key storage. We automate the -- traditionally very labor-intensive -- reverse engineering and data extraction process. To that end, we demonstrate that black-box measurements captured using laser-assisted SCA techniques from a training device with known key can be used to profile the device for a later key prediction on other victim devices with unknown keys. To showcase the potential of our approach, we target keys on three different hardware platforms, which are utilized as RoT in different products.