Mathias Oberhuber (Graz University of Technology), Martin Unterguggenberger (Graz University of Technology), Lukas Maar (Graz University of Technology), Andreas Kogler (Graz University of Technology), Stefan Mangard (Graz University of Technology)

Software-based power side-channel attacks are a significant security threat to modern computer systems, enabling adversaries to extract confidential information. Existing attacks typically exploit direct power signals from dedicated interfaces, as demonstrated in the PLATYPUS attack, or power-dependent timing variations, as in the case of the Hertzbleed attack. As access to direct power signals is meanwhile restricted on more and more platforms, an important question is whether other exploitable power-related signals exist beyond timing proxies.

In this paper, we show that Android mobile devices expose numerous power-related signals that allow power side-channel attacks. We systematically analyze unprivileged sensors provided by the Android sensor framework on multiple devices and show that these sensors expose parasitic influences of the power consumption. Our results include new insights into Android sensor leakage, particularly a novel leakage primitive: the rotation dependent power leakage of the geomagnetic rotation vector sensor. We extensively evaluate the exposed sensors for different information leakage types. We compare them with the corresponding ground truth, achieving correlations greater than 0.9 for some of our tested sensors. In extreme cases, we observe not only statistical results but also, e.g., changes in a compass app’s needle by approximately 30° due to CPU stress. Additionally, we evaluate the capabilities of our identified leakage primitives in two case studies: As a remote attacker via the Google Chrome web browser and as a local attacker running inside an installed app. In particular, we present an end-to-end pixel-stealing attack on different Android devices that effectively circumvents the browser’s cross-origin isolation with a leakage rate of 5 - 10 s per pixel. Lastly, we demonstrate a proof-of-concept AES attack, leaking individual key bytes using our newly discovered leakage primitive.

View More Papers

Understanding Data Importance in Machine Learning Attacks: Does Valuable...

Rui Wen (CISPA Helmholtz Center for Information Security), Michael Backes (CISPA Helmholtz Center for Information Security), Yang Zhang (CISPA Helmholtz Center for Information Security)

Read More

SCRUTINIZER: Towards Secure Forensics on Compromised TrustZone

Yiming Zhang (Southern University of Science and Technology and The Hong Kong Polytechnic University), Fengwei Zhang (Southern University of Science and Technology), Xiapu Luo (The Hong Kong Polytechnic University), Rui Hou (Institute of Information Engineering, Chinese Academy of Sciences), Xuhua Ding (Singapore Management University), Zhenkai Liang (National University of Singapore), Shoumeng Yan (Ant Group), Tao…

Read More

QMSan: Efficiently Detecting Uninitialized Memory Errors During Fuzzing

Matteo Marini (Sapienza University of Rome), Daniele Cono D'Elia (Sapienza University of Rome), Mathias Payer (EPFL), Leonardo Querzoni (Sapienza University of Rome)

Read More

MingledPie: A Cluster Mingling Approach for Mitigating Preference Profiling...

Cheng Zhang (Hunan University), Yang Xu (Hunan University), Jianghao Tan (Hunan University), Jiajie An (Hunan University), Wenqiang Jin (Hunan University)

Read More