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http://hdl.handle.net/123456789/19006
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DC Field | Value | Language |
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dc.contributor.author | Salman Jan | - |
dc.contributor.author | Shahrulniza Musa | - |
dc.contributor.author | Toqeer Ali | - |
dc.contributor.author | Ali Alzahrani | - |
dc.date.accessioned | 2018-07-09T08:32:01Z | - |
dc.date.available | 2018-07-09T08:32:01Z | - |
dc.date.issued | 2018-07-09 | - |
dc.identifier.uri | http://ir.unikl.edu.my/jspui/handle/123456789/19006 | - |
dc.description | Venue : Malaysian Institute of Information Technology, Universiti Kuala Lumpur, Kuala Lumpur, Malaysia | en_US |
dc.description.abstract | Malware analysis for Android systems has been the focus of considerable research in the past few years due to the large customer base moving towards Android, which has attracted a corresponding number of malware writers. Several techniques have been used to detect the malicious behavior of Android applications as well as that of the complete system. Machine-learning techniques have been used in the past to assess the behavior of an application using either static or dynamic analysis | en_US |
dc.subject | Android security | en_US |
dc.subject | Malware detection | en_US |
dc.subject | Deep Learning | en_US |
dc.subject | DCGAN | en_US |
dc.title | Deep Convolutional Generative Adversarial Networks for Intent-based Dynamic Behavior Capture | en_US |
dc.type | Article | en_US |
dc.conference.name | International Conference on Information and Communication Technology (ICICTM) | en_US |
dc.conference.year | 2018 | en_US |
Appears in Collections: | Conference Paper |
Files in This Item:
File | Description | Size | Format | |
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deep convolutional.pdf | 16.34 kB | Adobe PDF | View/Open Request a copy |
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