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Improving Reliability for Detecting Anomalies in the MQTT Network by Applying Correlation Analysis for Feature Selection Using Machine Learning Techniques.

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Title: Improving Reliability for Detecting Anomalies in the MQTT Network by Applying Correlation Analysis for Feature Selection Using Machine Learning Techniques.
Authors: Imran1,2, imran.ali@dsu.edu.pk, Zuhairi, Megat Farez Azril1, megatfarez@unikl.edu.my, Ali, Syed Mubashir1,3, mubashir.ali@kiet.edu.pk, Shahid, Zeeshan4, Alam, Muhammad Mansoor1,5,6,7, Su'ud, Mazliham Mohd5, mazliham@mmu.edu.my
Source: Applied Sciences (2076-3417); Jun2023, Vol. 13 Issue 11, p6753, 26p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
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PubType: Academic Journal
PubTypeId: academicJournal
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=164214034
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        Value: 10.3390/app13116753
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      – Code: eng
        Text: English
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        PageCount: 26
        StartPage: 6753
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      – TitleFull: Improving Reliability for Detecting Anomalies in the MQTT Network by Applying Correlation Analysis for Feature Selection Using Machine Learning Techniques.
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            NameFull: Imran
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            NameFull: Zuhairi, Megat Farez Azril
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            NameFull: Ali, Syed Mubashir
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            NameFull: Shahid, Zeeshan
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            NameFull: Alam, Muhammad Mansoor
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            NameFull: Su'ud, Mazliham Mohd
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            – D: 01
              M: 06
              Text: Jun2023
              Type: published
              Y: 2023
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              Value: 13
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