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An automated closed-loop framework to enforce security policies from anomaly detection

dc.contributor.authorHenriques, João
dc.contributor.authorCaldeira, Filipe
dc.contributor.authorCruz, Tiago
dc.contributor.authorSimões, Paulo
dc.date.accessioned2022-11-18T11:49:28Z
dc.date.available2022-11-18T11:49:28Z
dc.date.issued2022-12
dc.date.updated2022-11-15T18:43:30Z
dc.description.abstractDue to the growing complexity and scale of IT systems, there is an increasing need to automate and streamline routine maintenance and security management procedures, to reduce costs and improve productivity. In the case of security incidents, the implementation and application of response actions require significant efforts from operators and developers in translating policies to code. Even if Machine Learning (ML) models are used to find anomalies, they need to be regularly trained/updated to avoid becoming outdated. In an evolving environment, a ML model with outdated training might put at risk the organization it was supposed to defend. To overcome those issues, in this paper we propose an automated closed-loop process with three stages. The first stage focuses on obtaining the Decision Trees (DT) that classify anomalies. In the second stage, DTs are translated into security Policies as Code based on languages recognized by the Policy Engine (PE). In the last stage, the translated security policies feed the Policy Engines that enforce them by converting them into specific instruction sets. We also demonstrate the feasibility of the proposed framework, by presenting an example that encompasses the three stages of the closed-loop process. The proposed framework may integrate a broad spectrum of domains and use cases, being able for instance to support the decide and the act stages of the ETSI Zero-touch Network & Service Management (ZSM) framework.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationHenriques, J., Caldeira, F., Cruz, T., & Simões, P. (2022). An automated closed-loop framework to enforce security policies from anomaly detection. Computers & Security, 123, 102949. https://doi.org/10.1016/j.cose.2022.102949pt_PT
dc.identifier.doi10.1016/j.cose.2022.102949pt_PT
dc.identifier.slugcv-prod-3075931
dc.identifier.urihttp://hdl.handle.net/10400.19/7411
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectAutomationpt_PT
dc.subjectPolicy as codept_PT
dc.subjectDecision treespt_PT
dc.subjectMachine learningpt_PT
dc.subjectZero-touch network and service management (ZSM)pt_PT
dc.titleAn automated closed-loop framework to enforce security policies from anomaly detectionpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleComputers & Securitypt_PT
oaire.citation.volume123pt_PT
person.familyNameMenoita Henriques
person.familyNameCaldeira
person.givenNameJoão Pedro
person.givenNameFilipe
person.identifierhttps://scholar.google.pt/citations?user=AExQrJwAAAAJ
person.identifierlXPmBvYAAAAJ
person.identifier.ciencia-idBB15-BFE2-17AA
person.identifier.ciencia-idCB11-8109-AB1D
person.identifier.orcid0000-0001-7380-9511
person.identifier.orcid0000-0001-7558-2330
person.identifier.scopus-author-id36023210300
rcaap.cv.cienciaidCB11-8109-AB1D | Filipe Caldeira
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication9b3258cd-a3d1-46f9-bc04-2bdd99d87014
relation.isAuthorOfPublicatione845705e-5b0b-4f70-9c53-c472ffd768d1
relation.isAuthorOfPublication.latestForDiscoverye845705e-5b0b-4f70-9c53-c472ffd768d1

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