International Association
for Cryptologic Research

Microcontrollers and SoC devices have widely been used in Internet of Things applications. This also brings the question whether they lead to new security threats unseen in traditional computing systems. In fact, almost all modern SoC chips, particularly in the IoT domain, contain both analog and digital components, for various sensing and transmission tasks. Traditional remote-accessible online systems do not have this property, which can potentially become a security vulnerability. In this paper we demonstrate that such mixed-signal components, namely ADCs, expose a new security threat that allows attackers with ADC access to deduce the activity of a CPU in the system. To prove the leakage, we perform leakage assessment on three individual microcontrollers from two different vendors with various ADC settings. After showing a correlation of CPU activity with ADC noise, we continue with a leakage assessment of modular exponentiation and AES. It is shown that for all of these devices, leakage occurs for at least one algorithm and configuration of the ADC. Finally, we show a full key recovery attack on AES that works despite of the limited ADC sampling rate. These results imply that even remotely accessible microcontroller systems should be equipped with proper countermeasures against power analysis attacks, or restrict access to ADC data.

With each new technology generation, the available resources on Field Programmable Gate Arrays increase, making them more attractive for partial access from multiple users. They get increasingly adopted as accelerators in various application domains, embedded in shared Systems on Chip or remote cloud services. Thus, some recent works have already explored Denial-of-Service and side-channel attacks, where an FPGA fabric is shared among multiple users. In this work, we show how fault attacks can be launched within an FPGA, through software-provided bitstreams alone. Excessive voltage drops can be generated from legitimate logic mapped into the FPGA to cause timing faults, reaching from spatially and logically isolated partitions of one to another user of the FPGA fabric. To cause this voltage drop, we first show how specific patterns to activate Ring Oscillators can cause timing failures in simple test designs on various FPGA boards. Subsequently, we analyze and adapt an existing fault model for the Advanced Encryption Standard to match the accuracy of our fault attack. In the same multi-user scenario, we show as a proof-of-concept how a successful Differential Fault Analysis attack on an AES module can be launched. We perform experiments on three FPGA boards of the same model and confirm that the attack adapts to all systems and is successful under process variation, but with different susceptibility to faults. The paper is concluded by validating the attack on another platform, and analyzing the vulnerability based on a timing analysis, proving the applicability to different devices.