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Using data mining techniques to explore security issues in smart living environments in Twitter

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Using data mining techniques to explore security issues in smart living environments in Twitter

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dc.contributor.author Jose-Ramon Saura es_ES
dc.contributor.author Palacios Marqués, Daniel es_ES
dc.contributor.author Ribeiro-Soriano, Domingo es_ES
dc.date.accessioned 2022-03-03T19:02:32Z
dc.date.available 2022-03-03T19:02:32Z
dc.date.issued 2021-11-01 es_ES
dc.identifier.issn 0140-3664 es_ES
dc.identifier.uri http://hdl.handle.net/10251/181226
dc.description.abstract [EN] In present-day in consumers' homes, there are millions of Internet-connected devices that are known to jointly represent the Internet of Things (IoT). The development of the IoT industry has led to the emergence of connected devices and home assistants that create smart living environments. However, the continuously generated data accumulated by these connected devices create security issues and raise user's privacy concerns. The present study aims to explore the main security issues in smart living environments using data mining techniques. To this end, we applied a three-sentence data mining analysis of 9,38,258 tweets collected from Twitter under the user-generated data (UGD) framework. First, sentiment analysis was applied using Textblob which was tested with support vector classifier, multinomial naive bayes, logistic regression, and random forest classifier; as a result, the analyzed tweets were divided into those expressing positive, negative, and neutral sentiment. Next, a Latent Dirichlet Allocation (LDA) algorithm was applied to divide the sample into topics related to security issues in smart living environments. Finally, the insights were extracted by applying a textual analysis process in Python validated with the analysis of frequency and weighted percentage variables and calculating the statistical measure known as mutual information (MI) to analyze the identified n-grams (unigrams and bigrams). As a result of the research 10 topics were identified in which we found that the main security issues are malware, cybersecurity attacks, data storing vulnerabilities, the use of testing software in IoT, and possible leaks due to the lack of user experience. We discussed different circumstances and causes that may affect user security and privacy when using IoT devices and emphasized the importance of UGC in the processing of personal data of IoT device users. es_ES
dc.description.sponsorship In gratitude to the Ministry of Science, Innovation and Universities, Spain and the European Regional Development Fund: RTI2018-096295-B-C22. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Computer Communications es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Home assistant es_ES
dc.subject IoT es_ES
dc.subject Sentiment analysis es_ES
dc.subject Data mining es_ES
dc.subject Twitter es_ES
dc.subject UGC es_ES
dc.subject.classification ORGANIZACION DE EMPRESAS es_ES
dc.title Using data mining techniques to explore security issues in smart living environments in Twitter es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.comcom.2021.08.021 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-096295-B-C22/ES/DIGITALIZACION Y APLICACION DE NUEVOS MODELOS DE NEGOCIO Y GOBERNANZA A LA EMPRESA COLABORATIVA/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses es_ES
dc.description.bibliographicCitation Jose-Ramon Saura; Palacios Marqués, D.; Ribeiro-Soriano, D. (2021). Using data mining techniques to explore security issues in smart living environments in Twitter. Computer Communications. 179:285-295. https://doi.org/10.1016/j.comcom.2021.08.021 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.comcom.2021.08.021 es_ES
dc.description.upvformatpinicio 285 es_ES
dc.description.upvformatpfin 295 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 179 es_ES
dc.relation.pasarela S\456022 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder European Regional Development Fund es_ES


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