Network Security Data Analytics Architecture for Logged Events
| dc.contributor.author | DeYoung, Mark E. | en |
| dc.contributor.author | Marchany, Randolph C. | en |
| dc.contributor.author | Tront, Joseph G. | en |
| dc.contributor.department | Electrical and Computer Engineering | en |
| dc.date.accessioned | 2017-04-18T16:29:55Z | en |
| dc.date.available | 2017-04-18T16:29:55Z | en |
| dc.date.issued | 2017-01-04 | en |
| dc.description.abstract | Data-driven network security and information security efforts have decades long history. The deluge of logged events from network mid-points and end-points coupled with unprecedented temporal depth in data retention are driving an emerging market for automated cognitive security products. Historically, new technologies like this are delivered as non-contextualized black boxes. We frame network security data analytics within the context of intelligence activities and products and go on to propose network security data analytics as a framework to develop and evaluate cognitive security products that can satisfy operational needs. Finally, we discuss functional design requirements, limiting factors, and initial observations. | en |
| dc.description.notes | The paper was accepted as a long paper at HICSS 50 and was presented in the Symposium on Cybersecurity and Data Analytics on January 4 2017. | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.orcid | 0000-0002-6435-1980 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/77421 | en |
| dc.language.iso | en | en |
| dc.rights | Creative Commons Attribution-NonCommercial-NoDerivs 3.0 United States | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | en |
| dc.subject | Network Security | en |
| dc.subject | Data Analytics Architecture | en |
| dc.subject | Logged Events | en |
| dc.title | Network Security Data Analytics Architecture for Logged Events | en |
| dc.type | Report | en |
| dc.type.dcmitype | Text | en |