dc.contributor.author | Joback, Emily | |
dc.contributor.author | Shing, Leslie | |
dc.contributor.author | Alperin, Kenneth | |
dc.contributor.author | Gomez, Steven | |
dc.contributor.author | Jorgensen, Steven | |
dc.contributor.author | Elkin, Gabe | |
dc.date.accessioned | 2022-11-15T18:17:56Z | |
dc.date.available | 2022-11-15T18:17:56Z | |
dc.date.issued | 2020-12-07 | |
dc.identifier.isbn | 978-1-4503-8714-9 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/146469 | |
dc.publisher | ACM|2020 Workshop in DYnamic and Novel Advances in Machine Learning and Intelligent Cyber Security | en_US |
dc.relation.isversionof | https://doi.org/10.1145/3477997.3478007 | en_US |
dc.rights | Creative Commons Attribution 4.0 International license | en_US |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
dc.source | ACM|2020 Workshop in DYnamic and Novel Advances in Machine Learning and Intelligent Cyber Security | en_US |
dc.title | A Statistical Approach to Detecting Low-Throughput Exfiltration through the Domain Name System Protocol | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Joback, Emily, Shing, Leslie, Alperin, Kenneth, Gomez, Steven, Jorgensen, Steven et al. 2020. "A Statistical Approach to Detecting Low-Throughput Exfiltration through the Domain Name System Protocol." | |
dc.contributor.department | Lincoln Laboratory | |
dc.identifier.mitlicense | PUBLISHER_CC | |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
dc.date.updated | 2022-11-03T13:08:57Z | |
dc.language.rfc3066 | en | |
dc.rights.holder | The author(s) | |
dspace.date.submission | 2022-11-03T13:08:57Z | |
mit.license | PUBLISHER_CC | |
mit.metadata.status | Authority Work and Publication Information Needed | en_US |