Improving malicious detection rate for Facebook application in OSN platform
Online social networks (OSNs) have become the new vector for cybercrime, and hackers are finding new ways to propagate spam and malware on these platforms, which we refer to as social malware. As we show here, social malware cannot be identified with existing security mechanisms (e.g., URL blacklist...
محفوظ في:
المؤلف الرئيسي: | Angamuthu, Laavanya |
---|---|
التنسيق: | أطروحة |
اللغة: | English |
منشور في: |
2018
|
الموضوعات: | |
الوصول للمادة أونلاين: | http://psasir.upm.edu.my/id/eprint/68968/1/FSKTM%202018%2041%20IR.pdf |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
An artificial co-stimulation classifier for malicious API calls classification in portable executable malwares /
بواسطة: Abdulla, Saman Mirza
منشور في: (2013) -
A malware analysis and detection system for mobile devices /
بواسطة: Feizollah, Ali
منشور في: (2017) -
Behavior analysis and development of the detection algorithm and application prototype to detect the presence of the premium short message service (SMS) abusers malware on the android platform /
بواسطة: Syed Mohd Hazrul bin Syed Salim
منشور في: (2013) -
A dynamic malware detection in cloud platform
بواسطة: Lee, Nani Yer Fui
منشور في: (2019) -
Web application scanning for malware attack detection with provide appropriate incident report by using hybrid method
بواسطة: Abdul Razak, Aina Nabila
منشور في: (2019)