Malware visualizer: A web apps malware family classification with machine learning
Within the past few years, malware has been a serious threat to the security and privacy of all mobile phone users. Due to the popularity of smartphones, primarily Android, this makes them a very viable target for spreading malware. Many solutions in the past have proven to be ineffective and result...
Main Authors: | Mohd Zamri, Osman, Ahmad Firdaus, Zainal Abidin, Rahiwan Nazar, Romli |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/34538/1/Malware%20visualizer_A%20web%20apps%20malware%20family%20classification%20with%20machine%20learning.CITREX2021..pdf |
Similar Items
-
Maldroid- attribute selection analysis for malware classification
by: Rahiwan Nazar, Romli, et al.
Published: (2019) -
Efficient feature selection analysis for accuracy malware classification
by: Rahiwan Nazar, Romli, et al.
Published: (2021) -
CAGDEEP : Mobile malware analysis using force atlas 2 with strong gravity call graph and deep learning
by: Nur Khairani, Kamarudin, et al.
Published: (2023) -
Android mobile malware detection system using fuzzy AHP
by: Juliza, Mohamad Arif, et al.
Published: (2021) -
Android: S-Based Technique in Mobile Malware Detection
by: Rahiwan Nazar, Romli, et al.
Published: (2018)