| dc.contributor.author | Asprusten, Markus Leira | en_GB |
| dc.contributor.author | Gjerstad, Julie Lidahl | en_GB |
| dc.contributor.author | Grov, Gudmund | en_GB |
| dc.contributor.author | Kjellstadli, Espen Hammer | en_GB |
| dc.contributor.author | Flood, Robert | en_GB |
| dc.contributor.author | Clausen, Henry | en_GB |
| dc.contributor.author | Aspinall, David | en_GB |
| dc.date.accessioned | 2022-02-02T08:00:24Z | |
| dc.date.accessioned | 2022-02-03T13:47:11Z | |
| dc.date.available | 2022-02-02T08:00:24Z | |
| dc.date.available | 2022-02-03T13:47:11Z | |
| dc.date.issued | 2022-01-24 | |
| dc.identifier.citation | Asprusten, Gjerstad, Grov, Kjellstadli, Flood, Clausen, Aspinall. A containerised approach to labelled C&C traffic . Norsk Informasjonssikkerhetskonferanse (NISK). 2021 | en_GB |
| dc.identifier.uri | http://hdl.handle.net/20.500.12242/2989 | |
| dc.description | - | en_GB |
| dc.description.abstract | A challenge for data-driven methods for intrusion detection is the availability of high quality and realistic data, with ground truth at suitable level of granularity to train machine learning models. Here, we explore a container-based approach for simulating and labelling C&C traffic of real malware through a proof-of-concept implementation. | en_GB |
| dc.language.iso | en | en_GB |
| dc.relation.uri | https://ojs.bibsys.no/index.php/NIK/article/view/957 | |
| dc.subject | Deteksjon | en_GB |
| dc.subject | Informasjonssikkerhet | en_GB |
| dc.subject | Maskinlæring | en_GB |
| dc.title | A containerised approach to labelled C&C traffic | en_GB |
| dc.type | Article | en_GB |
| dc.date.updated | 2022-02-02T08:00:24Z | |
| dc.identifier.cristinID | 1989685 | |
| dc.source.issn | 1893-6563 | |
| dc.source.issn | 1894-7735 | |
| dc.type.document | Journal article | |
| dc.relation.journal | Norsk Informasjonssikkerhetskonferanse (NISK) | |