JitSCA: Jitter-based Side-Channel Analysis in Picoscale Resolution
DOI:
https://doi.org/10.46586/tches.v2023.i3.294-320Keywords:
side-channel, jitter, power, timing, galvanically isolatedAbstract
In safety and security conscious environments, isolated communication channels are often deemed necessary. Galvanically isolated communication channels are typically expected not to allow physical side-channel attacks through that channel. However, in this paper, we show that they can inadvertently leak side channel information in the form of minuscule jitter on the communication signal. We observe worst-case signal jitter within 54 ± 45 ps using an FPGA-based receiver employing a time-to-digital converter (TDC), which is a higher time resolution than a typical oscilloscope can measure, while in many other systems such measurements are also possible. A transmitter device runs a cryptographic accelerator, while we connect an FPGA on the receiver side and measure the signal jitter using a TDC. We can indeed show sufficient side-channel leakage in the jitter of the signal by performing a key recovery of an AES accelerator running on the transmitter. Furthermore, we compare this leakage to a power side channel also measured with a TDC and prove that the timing jitter alone contains sufficient side-channel information. While for an on-chip power analysis attack about 27k traces are needed for key recovery, our cross-device jitter-based attack only needs as few as 47k traces, depending on the setup. Galvanic isolation does not change that significantly. That is an increase by only 1.7x, showing that fine-grained jitter timing information can be a very potent attack vector even under galvanic isolation. In summary, we introduce a new side-channel attack vector that can leak information in many presumably secure systems. Communication channels can inadvertently leak information through tiny timing variations, known as signal jitter. This could affect millions of devices and needs to be considered.
Downloads
Published
Issue
Section
License
Copyright (c) 2023 Kai Schoos, Sergej Meschkov, Mehdi B. Tahoori, Dennis R. E. Gnad
This work is licensed under a Creative Commons Attribution 4.0 International License.