Dimension Reduction For Classification Using Principal Component Analysis (PCA) To Detect Malicious Executables
The development of cyberspace is not only facilitate people's lives. It should also be in line with security awareness related to personal and enterprise systems. Estimates of the number of new malware in 2013 reached 600 million, and has grown rapidly in recent years. Malware can attack a wide...
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| التنسيق: | أطروحة |
| اللغة: | English English |
| منشور في: |
2017
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://eprints.utem.edu.my/id/eprint/20734/1/Dimension%20Reduction%20For%20Classification%20Using%20Principal%20Component%20Analysis%20%28PCA%29%20To%20Detect%20Malicious%20Executables%20-%20Zalifh%20Jamal%20-%2024%20Pages.pdf http://eprints.utem.edu.my/id/eprint/20734/2/Dimension%20Reduction%20For%20Classification%20Using%20Principal%20Component%20Analysis%20%28PCA%29%20To%20Detect%20Malicious%20Executables.pdf |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
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الانترنت
http://eprints.utem.edu.my/id/eprint/20734/1/Dimension%20Reduction%20For%20Classification%20Using%20Principal%20Component%20Analysis%20%28PCA%29%20To%20Detect%20Malicious%20Executables%20-%20Zalifh%20Jamal%20-%2024%20Pages.pdfhttp://eprints.utem.edu.my/id/eprint/20734/2/Dimension%20Reduction%20For%20Classification%20Using%20Principal%20Component%20Analysis%20%28PCA%29%20To%20Detect%20Malicious%20Executables.pdf