About: Device Identification Using Discrete Wavelet Transform

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type	http://eprints.org/ontology/ConferenceItemEPrint http://eprints.org/ontology/EPrint Article Academic Article
seeAlso	HTML Summary of #90749 Device Identification Using Discrete Wavelet Transform
sameAs	Device Identification Using Discrete Wavelet Transform
http://eprints.org/ontology/hasAccepted	Device Identification Using Discrete Wavelet Transform (PDF)
http://eprints.org/ontology/hasDocument	Device Identification Using Discrete Wavelet Transform (PDF) Device Identification Using Discrete Wavelet Transform (Other) Device Identification Using Discrete Wavelet Transform (Other) Device Identification Using Discrete Wavelet Transform (Other) Device Identification Using Discrete Wavelet Transform (Other) Device Identification Using Discrete Wavelet Transform (Other)
dc:hasVersion	Device Identification Using Discrete Wavelet Transform (PDF)
Title	Device Identification Using Discrete Wavelet Transform
described by	https://demo.openlinksw.com/about/id/entity/https/raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
Date	2022-01-05
Creator	Pooja Khanna Supriya Yadav Gareth Howells
status	peer reviewed published
Publisher	IEEE
abstract	This paper investigates the effectiveness of employing measured hardware features mapped into the frequency domain for devices identification. The technique is to utilize Discrete Wavelet Transform (DWT) coefficients as distinguishing features. The DWT coefficients address the degree of relationship between the investigated features and the wavelet function at different occurrences of time. Therefore, DWT coefficients carry useful temporal information about the transient activity of the investigated wavelet features. We study the impacts of utilizing different wavelet functions (Coiflets, Haar and Symlets) on the performance of the device identification system. This system yields 92.5 % of accuracy using Sym6 wavelet. A comparison is made of the accuracy of wavelet features and raw features with standard classifiers.
Is Part Of	https://kar.kent.ac.uk/id/repository
Subject	QA 76 Software, computer programming, TA1637 Image processing
list of authors	https://kar.kent.ac.uk/id/eprint/90749#authors
presented at	7th International Conference on Engineering and Emerging Technologies (ICEET)
is topic of	https://raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
is primary topic of	HTML Summary of #90749 Device Identification Using Discrete Wavelet Transform

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