Malware detection
In the present work the behavior of malicious software is studied, the security challenges are understood, and an attempt is made to detect the malware behavior automatically using dynamic approach. Various classification techniques are studied. Malwares are then grouped according to these technique...
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| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Hamburg
Anchor Academic Publishing
2017
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| Schriftenreihe: | Compact
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| Schlagworte: | |
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Tag hinzufügen | Zusammenfassung: | In the present work the behavior of malicious software is studied, the security challenges are understood, and an attempt is made to detect the malware behavior automatically using dynamic approach. Various classification techniques are studied. Malwares are then grouped according to these techniques and malware with unknown characteristics are clustered into an unknown group. The classifiers used in this research are k-Nearest Neighbors (kNN), J48 Decision Tree, and n-grams. |
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| Beschreibung: | 66 Seiten Illustrationen |
| ISBN: | 9783960672081 978-3-96067-208-1 |