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Detecting Cryptojacking Web Threats: An Approach with Autoencoders and Deep Dense Neural Networks.

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Title: Detecting Cryptojacking Web Threats: An Approach with Autoencoders and Deep Dense Neural Networks.
Authors: Hernandez-Suarez, Aldo1, alhernandezsu@ipn.mx, Sanchez-Perez, Gabriel1, gasanchezp@ipn.mx, Toscano-Medina, Linda K.1, ltoscano@ipn.mx, Olivares-Mercado, Jesus1, jolivares@ipn.mxjportillop@ipn.mx, Portillo-Portilo, Jose1, javaloso@ipn.mx, Avalos, Juan-Gerardo1, García Villalba, Luis Javier2, jolivares@ipn.mx
Source: Applied Sciences (2076-3417); Apr2022, Vol. 12 Issue 7, p3234-3234, 28p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 156248738
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Detecting Cryptojacking Web Threats: An Approach with Autoencoders and Deep Dense Neural Networks.
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  Data: <searchLink fieldCode="JN" term="%22Applied+Sciences+%282076-3417%29%22">Applied Sciences (2076-3417)</searchLink>; Apr2022, Vol. 12 Issue 7, p3234-3234, 28p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=156248738
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        Value: 10.3390/app12073234
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        Text: English
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              Text: Apr2022
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