Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 713

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Controlled-Channel Attacks: Deterministic Side Channels for Untrusted Operating Systems

Open access
Xu, Yuanzhong, Cui, Weidong, Peinado, Marcus·2015·2015 IEEE Symposium on Security and Privacy

Abstract

The presence of large numbers of security vulnerabilities in popular feature-rich commodity operating systems has inspired a long line of work on excluding these operating systems from the trusted computing base of applications, while retaining many of their benefits. Legacy applications continue to run on the untrusted operating system, while a small hyper visor or trusted hardware prevents the operating system from accessing the applications' memory. In this paper, we introduce controlled-channel attacks, a new type of side-channel attack that allows an untrusted operating system to extract large amounts of sensitive information from protected applications on systems like Overshadow, Ink Tag or Haven. We implement the attacks on Haven and Ink Tag and demonstrate their power by extracting complete text documents and outlines of JPEG images from widely deployed application libraries. Given these attacks, it is unclear if Over shadow's vision of protecting unmodified legacy applications from legacy operating systems running on off-the-shelf hardware is still tenable.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/sp.2015.45

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 713

Metadata

Authors
Xu, Y., Cui, W., & Peinado, M.
Venue
2015 IEEE Symposium on Security and Privacy
Publisher
IEEE
Published
2015-05
Pages
640-656
ISSN
1081-6011 (ISSN-L)
OpenAlex
W2150620897
Cited by
713
References
1
FWCI
44.70
Type
conference paper
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Controlled-Channel Attacks: Deterministic Side Channels for Untrusted Operating Systems. https://app.cochat.ai/papers/10.1109/sp.2015.45
The paper
Xu, Y., Cui, W., & Peinado, M. (2015). Controlled-Channel Attacks: Deterministic Side Channels for Untrusted Operating Systems. 2015 IEEE Symposium on Security and Privacy. https://doi.org/10.1109/sp.2015.45

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.