| dc.contributor.author | Wang, Ping | |
| dc.contributor.author | Nagaraja, Shishir | |
| dc.contributor.author | Bourquard, Aur?lien | |
| dc.contributor.author | Gao, Haichang | |
| dc.contributor.author | Yan, Jeff | |
| dc.date.accessioned | 2025-12-16T18:53:02Z | |
| dc.date.available | 2025-12-16T18:53:02Z | |
| dc.date.issued | 2025-11-26 | |
| dc.identifier.issn | 0360-0300 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/164342 | |
| dc.description.abstract | Acoustic side channels (ASCs) have been discovered for several decades, highlighting the tangible security risks posed by unintended sound emissions from computing and electronic systems. Their existence has drawn considerable attention from researchers, driving rapid progress in both attack methodologies and defense mechanisms across a wide range of scenarios. In this paper, we provide a state-of-the-art analysis of ASCs, covering all the significant academic research in the area. First, we clarify existing ambiguities and conceptual confusion, proposing a clear definition of ASC. Second, we analyse the characteristics of known ASCs, discuss their security implications, and propose the first taxonomy. Next, we summarize attack techniques, discuss countermeasures, and identify areas for future research. We also link side channels and inverse problems, two fields that appear to be completely isolated from each other but have deep connections. | en_US |
| dc.publisher | ACM | en_US |
| dc.relation.isversionof | http://dx.doi.org/10.1145/3778350 | en_US |
| dc.rights | Creative Commons Attribution | en_US |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
| dc.source | Association for Computing Machinery | en_US |
| dc.title | SoK: Acoustic Side Channels | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Ping Wang, Shishir Nagaraja, Aurélien Bourquard, Haichang Gao, and Jeff Yan. 2025. SoK: Acoustic Side Channels. ACM Comput. Surv. Just Accepted (November 2025). | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Magnetic Resonance Imaging Group | en_US |
| dc.relation.journal | ACM Computing Surveys | en_US |
| dc.identifier.mitlicense | PUBLISHER_POLICY | |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dc.date.updated | 2025-12-01T09:55:28Z | |
| dc.language.rfc3066 | en | |
| dc.rights.holder | The author(s) | |
| dspace.date.submission | 2025-12-01T09:55:28Z | |
| mit.license | PUBLISHER_CC | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |