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dc.contributor.authorFlores, Adan
dc.date.accessioned2020-05-13 18:26:23 (GMT)
dc.date.available2020-05-13 18:26:23 (GMT)
dc.date.issued2020-05-13
dc.date.submitted2020-04-27
dc.identifier.urihttp://hdl.handle.net/10012/15841
dc.description.abstractThis thesis presents a novel non-intrusive method of creating a map of black-box systems’ behavior to commands by observing the power consumption of the system. We expand our method in the form of a flexible framework which supports communication abstraction layer to send commands on different channels. The framework also integrates data processing and the opportunity of adding a validation module that framework users can utilize to detect anomalies in the system. The framework furthermore builds on the idea of anomaly detection by providing two operating modes: one for generating training data for machine learning models, and one for run-time validation of the system’s behavior. From the experiments, we confirm the effectiveness of the framework for creating a map of the system’s power consumption against a series of queries. Our experiments also show some of the challenges presented with this method when different commands induce similar behaviour in the system.en
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.subjectside channel behaviour analysisen
dc.subjectpower tracingen
dc.subject.lcshComputersen
dc.subject.lcshPower supplyen
dc.subject.lcshEfficiencyen
dc.subject.lcshEnergy consumptionen
dc.subject.lcshPower resourcesen
dc.subject.lcshData processingen
dc.titleNon-Intrusive system behavior tracing using power consumptionen
dc.typeMaster Thesisen
dc.pendingfalse
uws-etd.degree.departmentElectrical and Computer Engineeringen
uws-etd.degree.disciplineElectrical and Computer Engineeringen
uws-etd.degree.grantorUniversity of Waterlooen
uws-etd.degreeMaster of Applied Scienceen
uws.contributor.advisorFischmeister, Sebastian
uws.contributor.affiliation1Faculty of Engineeringen
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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