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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-30376
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dc.contributor.authorRüedlinger, Andreas-
dc.contributor.authorKlauser, Rebecca-
dc.contributor.authorLamprakis, Pavlos-
dc.contributor.authorHappe, Markus-
dc.contributor.authorTellenbach, Bernhard-
dc.contributor.authorVeyisoglu, Onur-
dc.contributor.authorTrammell, Ariane-
dc.date.accessioned2024-03-27T12:23:58Z-
dc.date.available2024-03-27T12:23:58Z-
dc.date.issued2024-
dc.identifier.isbn978-989-758-683-5de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/30376-
dc.description.abstractA sound understanding of the adversary in the form of cyber threat intelligence (CTI) is key to successful cyber defense. Various sources of CTI exist, however there is no state-of-the-art method to approximate feed quality in an automated and continuous way. In addition, finding, combining and maintaining relevant feeds is very laborious and impedes taking advantage of the full potential of existing feeds. We propose FeedMeter, a platform that collects, normalizes, and aggregates threat intelligence feeds and continuously monitors them using eight descriptive metrics that approximate the feed quality. The platform aims to reduce the workload of duplicated manual processing and maintenance tasks and shares valuable insights about threat intelligence feeds. Our evaluation of a FeedMeter prototype with more than 150 OSINT sources, conducted over four years, shows that the platform has a real benefit for the community and that the metrics are promising approximations of source quality. A comparison with a prevalent commercial threat intelligence feed further strengthens this finding.de_CH
dc.language.isoende_CH
dc.publisherSciTePressde_CH
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/de_CH
dc.subjectOpen source intelligence (OSINT)de_CH
dc.subjectCyber threat intelligence (CTI)de_CH
dc.subjectThreat feedde_CH
dc.subject.ddc005: Computerprogrammierung, Programme und Datende_CH
dc.titleFeedMeter : evaluating the quality of community-driven threat intelligencede_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
dc.identifier.doi10.5220/0012357600003648de_CH
dc.identifier.doi10.21256/zhaw-30376-
zhaw.conference.details10th International Conference on Information Systems Security and Privacy (ICISSP), Rome, Italy, 26-28 February 2024de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end66de_CH
zhaw.pages.start54de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedingsProceedings of the 10th International Conference on Information Systems Security and Privacy - ICISSPde_CH
zhaw.webfeedInformation Securityde_CH
zhaw.funding.zhawHostDetective – Next Generation Active and Passive Web Server Rating Systemde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Rüedlinger, A., Klauser, R., Lamprakis, P., Happe, M., Tellenbach, B., Veyisoglu, O., & Trammell, A. (2024). FeedMeter : evaluating the quality of community-driven threat intelligence [Conference paper]. Proceedings of the 10th International Conference on Information Systems Security and Privacy - ICISSP, 54–66. https://doi.org/10.5220/0012357600003648
Rüedlinger, A. et al. (2024) ‘FeedMeter : evaluating the quality of community-driven threat intelligence’, in Proceedings of the 10th International Conference on Information Systems Security and Privacy - ICISSP. SciTePress, pp. 54–66. Available at: https://doi.org/10.5220/0012357600003648.
A. Rüedlinger et al., “FeedMeter : evaluating the quality of community-driven threat intelligence,” in Proceedings of the 10th International Conference on Information Systems Security and Privacy - ICISSP, 2024, pp. 54–66. doi: 10.5220/0012357600003648.
RÜEDLINGER, Andreas, Rebecca KLAUSER, Pavlos LAMPRAKIS, Markus HAPPE, Bernhard TELLENBACH, Onur VEYISOGLU und Ariane TRAMMELL, 2024. FeedMeter : evaluating the quality of community-driven threat intelligence. In: Proceedings of the 10th International Conference on Information Systems Security and Privacy - ICISSP. Conference paper. SciTePress. 2024. S. 54–66. ISBN 978-989-758-683-5
Rüedlinger, Andreas, Rebecca Klauser, Pavlos Lamprakis, Markus Happe, Bernhard Tellenbach, Onur Veyisoglu, and Ariane Trammell. 2024. “FeedMeter : Evaluating the Quality of Community-Driven Threat Intelligence.” Conference paper. In Proceedings of the 10th International Conference on Information Systems Security and Privacy - ICISSP, 54–66. SciTePress. https://doi.org/10.5220/0012357600003648.
Rüedlinger, Andreas, et al. “FeedMeter : Evaluating the Quality of Community-Driven Threat Intelligence.” Proceedings of the 10th International Conference on Information Systems Security and Privacy - ICISSP, SciTePress, 2024, pp. 54–66, https://doi.org/10.5220/0012357600003648.


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