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

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 118 ) ) ) [post__not_in] => Array ( [0] => 19977 ) )

Probe-Me-Not: Protecting Pre-trained Encoders from Malicious Probing

Ruyi Ding (Northeastern University), Tong Zhou (Northeastern University), Lili Su (Northeastern University), Aidong Adam Ding (Northeastern University), Xiaolin Xu (Northeastern University), Yunsi Fei (Northeastern University)

Read More

Starshields for iOS: Navigating the Security Cosmos in Satellite...

Jiska Classen (Hasso Plattner Institute, University of Potsdam), Alexander Heinrich (TU Darmstadt, Germany), Fabian Portner (TU Darmstadt, Germany), Felix Rohrbach (TU Darmstadt, Germany), Matthias Hollick (TU Darmstadt, Germany)

Read More

Eclipse Attacks on Monero's Peer-to-Peer Network

Ruisheng Shi (Beijing University of Posts and Telecommunications), Zhiyuan Peng (Beijing University of Posts and Telecommunications), Lina Lan (Beijing University of Posts and Telecommunications), Yulian Ge (Beijing University of Posts and Telecommunications), Peng Liu (Penn State University), Qin Wang (CSIRO Data61), Juan Wang (Wuhan University)

Read More

Formally Verifying the Newest Versions of the GNSS-centric TESLA...

Ioana Boureanu, Stephan Wesemeyer (Surrey Centre for Cyber Security, University of Surrey)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)