-
Notifications
You must be signed in to change notification settings - Fork 9
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
Showing
3 changed files
with
32 additions
and
0 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,17 @@ | ||
@inproceedings{10.1145/3576915.3623112, | ||
author = {Geimer, Antoine and Vergnolle, Math\'{e}o and Recoules, Fr\'{e}d\'{e}ric and Daniel, Lesly-Ann and Bardin, S\'{e}bastien and Maurice, Cl\'{e}mentine}, | ||
title = {A Systematic Evaluation of Automated Tools for Side-Channel Vulnerabilities Detection in Cryptographic Libraries}, | ||
year = {2023}, | ||
isbn = {9798400700507}, | ||
publisher = {Association for Computing Machinery}, | ||
address = {New York, NY, USA}, | ||
url = {https://doi.org/10.1145/3576915.3623112}, | ||
doi = {10.1145/3576915.3623112}, | ||
abstract = {To protect cryptographic implementations from side-channel vulnerabilities, developers must adopt constant-time programming practices. As these can be error-prone, many side-channel detection tools have been proposed. Despite this, such vulnerabilities are still manually found in cryptographic libraries. While a recent paper by Jancar et al. shows that developers rarely perform side-channel detection, it is unclear if existing detection tools could have found these vulnerabilities in the first place.To answer this question we surveyed the literature to build a classification of 34 side-channel detection frameworks. The classification we offer compares multiple criteria, including the methods used, the scalability of the analysis or the threat model considered. We then built a unified common benchmark of representative cryptographic operations on a selection of 5 promising detection tools. This benchmark allows us to better compare the capabilities of each tool, and the scalability of their analysis. Additionally, we offer a classification of recently published side-channel vulnerabilities. We then test each of the selected tools on benchmarks reproducing a subset of these vulnerabilities as well as the context in which they appear. We find that existing tools can struggle to find vulnerabilities for a variety of reasons, mainly the lack of support for SIMD instructions, implicit flows, and internal secret generation. Based on our findings, we develop a set of recommendations for the research community and cryptographic library developers, with the goal to improve the effectiveness of side-channel detection tools.}, | ||
booktitle = {Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security}, | ||
pages = {1690–1704}, | ||
numpages = {15}, | ||
keywords = {automated detection, side-channels, vulnerabilities}, | ||
location = {<conf-loc>, <city>Copenhagen</city>, <country>Denmark</country>, </conf-loc>}, | ||
series = {CCS '23} | ||
} |
Binary file not shown.