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Anomaly detection through keystroke and tap dynamics implemented via machine learning algorithms.

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Bibliographic Details
Title: Anomaly detection through keystroke and tap dynamics implemented via machine learning algorithms.
Authors: JAWED, Hani1, ZIAD, Zara1, KHAN, Muhammad Mubashir1, mmkhan@neduet.edu.pk, ASRAR, Maheen1
Source: Turkish Journal of Electrical Engineering & Computer Sciences; 2018, Vol. 26 Issue 4, p1698-1709, 12p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 131285625
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PubType: Academic Journal
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  Data: Anomaly detection through keystroke and tap dynamics implemented via machine learning algorithms.
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  Data: <searchLink fieldCode="JN" term="%22Turkish+Journal+of+Electrical+Engineering+%26+Computer+Sciences%22">Turkish Journal of Electrical Engineering & Computer Sciences</searchLink>; 2018, Vol. 26 Issue 4, p1698-1709, 12p
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.3906/elk-1711-410
    Languages:
      – Code: eng
        Text: English
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        PageCount: 12
        StartPage: 1698
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      – TitleFull: Anomaly detection through keystroke and tap dynamics implemented via machine learning algorithms.
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            NameFull: JAWED, Hani
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            NameFull: ZIAD, Zara
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            NameFull: KHAN, Muhammad Mubashir
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              Text: 2018
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              Y: 2018
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              Value: 26
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              Value: 4
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            – TitleFull: Turkish Journal of Electrical Engineering & Computer Sciences
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