Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection
Intrusion Detection (ID) in the context of computer networks is an essential technique in modern defense-in-depth security strategies. As such, Intrusion Detection Systems (IDSs) have received tremendous attention from security researchers and professionals. An important concept in ID is anomaly det...
محفوظ في:
المؤلف الرئيسي: | Ghanem, Waheed Ali Hussein Mohammed |
---|---|
التنسيق: | أطروحة |
اللغة: | English |
منشور في: |
2019
|
الموضوعات: | |
الوصول للمادة أونلاين: | http://eprints.usm.my/46632/1/WaheedGhanem-Phd201924.pdf |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Feature Selection Method Based On Hybrid Filter-Metaheuristic Wrapper Approach
بواسطة: Jothi, Neesha
منشور في: (2020) -
Temporal Based Network Intrusion Detection With Recurrent Neural Network And Random Forest
بواسطة: Lee, Nicholas Ming Ze
منشور في: (2019) -
Multithreaded Scalable Matching Algorithm For Intrusion Detection Systems
بواسطة: Hnaif, Adnan Ahmad Abdelfattah
منشور في: (2010) -
Adapting And Hybrid Ising Harmony Search With Metaheuristic Components For University Course Timetabling
بواسطة: Al-Betar, Mohammed Azmi
منشور في: (2010) -
Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function
بواسطة: Shehab, Mohammad Mohammad Said
منشور في: (2018)