Evaluation of AI-based Malware Detection in IoT Network Traffic

Prazeres, Nuno; Costa, Rogério Luís de C.; Santos, Leonel; Rabadão, Carlos

Publication

Evaluation of AI-based Malware Detection in IoT Network Traffic

2022Conference object

dc.contributor.author	Prazeres, Nuno
dc.contributor.author	Costa, Rogério Luís de C.
dc.contributor.author	Santos, Leonel
dc.contributor.author	Rabadão, Carlos
dc.date.accessioned	2023-03-06T13:46:46Z
dc.date.available	2023-03-06T13:46:46Z
dc.date.issued	2022
dc.date.updated	2023-03-02T15:07:37Z
dc.description	Artigo publicado em: Proceedings of the 19th International Conference on Security and Cryptography - SECRYPT, 580-585, ISBN 978-989-758-590-6; ISSN 2184-7711, pages 580-585, 2022. DOI: 10.5220/0011279600003283.	pt_PT
dc.description	A 19ª Conferência Internacional sobre Segurança e Criptografia, foi realizada nos dias 11-13 de julho, de 2022, em Lisboa, Portugal.
dc.description.abstract	Internet of Things (IoT) devices have become day-to-day technologies. They collect and share a large amount of data, including private data, and are an attractive target of potential attackers. On the other hand, machine learning has been used in several contexts to analyze and classify large volumes of data. Hence, using machine learning to classify network traffic data and identify anomalous traffic and potential attacks promises. In this work, we use deep and traditional machine learning to identify anomalous traffic in the IoT-23 dataset, which contains network traffic from real-world equipment. We apply feature selection and encoding techniques and expand the types of networks evaluated to improve existing results from the literature. We compare the performance of algorithms in binary classification, which separates normal from anomalous traffic, and in multiclass classification, which aims to identify the type of attack.	pt_PT
dc.description.version	info:eu-repo/semantics/publishedVersion	pt_PT
dc.identifier.citation	Prazeres, Nuno, Costa, Rogerio Luís de C., Santos, Leonel, and Rabadao, Carlos. ˜ Evaluation of AI-based Malware Detection in IoT Network Traffic. In Proceedings of the 19th International Conference on Security and Cryptography (SECRYPT 2022), pages 580-585 - DOI: 10.5220/0011279600003283 - ISBN: 978-989- 758-590-6; ISSN: 2184-7711	pt_PT
dc.identifier.doi	http://dx.doi.org/10.5220/0011279600003283	pt_PT
dc.identifier.isbn	978-989-758-590-6
dc.identifier.issn	2184-7711
dc.identifier.slug	cv-prod-3056330
dc.identifier.uri	http://hdl.handle.net/10400.8/8175
dc.language.iso	eng	pt_PT
dc.peerreviewed	yes	pt_PT
dc.publisher	Science and Technology Publications	pt_PT
dc.relation	UIDB/04524/2020	pt_PT
dc.relation	CEECI2018/FCT	pt_PT
dc.relation.publisherversion	https://www.scitepress.org/PublicationsDetail.aspx?ID=v02bUYG54IM=&t=1	pt_PT
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	pt_PT
dc.subject	Internet of Things	pt_PT
dc.subject	Machine Learning	pt_PT
dc.subject	Intrusion Detection Systems	pt_PT
dc.subject	Cybersecurity	pt_PT
dc.title	Evaluation of AI-based Malware Detection in IoT Network Traffic	pt_PT
dc.type	conference object
dspace.entity.type	Publication
oaire.citation.conferencePlace	Lisboa, Portugal	pt_PT
oaire.citation.endPage	585	pt_PT
oaire.citation.startPage	580	pt_PT
oaire.citation.title	Proceedings of the 19th International Conference on Security and Cryptography	pt_PT
oaire.citation.volume	1	pt_PT
person.familyName	Gonçalves dos Prazeres
person.familyName	de Carvalho Costa
person.familyName	Simões Santos
person.familyName	Rabadão
person.givenName	Nuno Alexandre
person.givenName	Rogério Luís
person.givenName	Leonel Filipe
person.givenName	Carlos
person.identifier.ciencia-id	7717-9573-0C0F
person.identifier.ciencia-id	C212-374B-3FF1
person.identifier.ciencia-id	2C1C-E900-6A57
person.identifier.orcid	0000-0003-1760-6220
person.identifier.orcid	0000-0003-2306-7585
person.identifier.orcid	0000-0002-6883-7996
person.identifier.orcid	0000-0001-7332-4397
person.identifier.rid	A-7940-2016
person.identifier.rid	M-3235-2013
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person.identifier.scopus-author-id	22433497800
rcaap.cv.cienciaid	7717-9573-0C0F \| Rogério Luís de Carvalho Costa
rcaap.rights	closedAccess	pt_PT
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