Improved Malware detection model with Apriori Association rule and particle swarm optimization
The incessant destruction and harmful tendency of malware on mobile devices has made malware detection an indispensable continuous field of research. Different matching/mismatching approaches have been adopted in the detection of malware which includes anomaly detection technique, misuse detection,...
Main Authors: | Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah |
---|---|
Format: | Article |
Language: | English English English |
Published: |
Hindawi Limited
2019
|
Subjects: | |
Online Access: | http://irep.iium.edu.my/79657/ http://irep.iium.edu.my/79657/ http://irep.iium.edu.my/79657/ http://irep.iium.edu.my/79657/3/79657_Improved%20Malware%20Detection.pdf http://irep.iium.edu.my/79657/1/79657_Improved%20Malware%20Detection_SCOPUS.pdf http://irep.iium.edu.my/79657/2/79657_Improved%20Malware%20Detection_WOS.pdf |
Similar Items
-
Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
by: Adebayo, Olawale Surajudeen, et al.
Published: (2014) -
Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
by: Adebayo, Olawale Surajudeen, et al.
Published: (2015) -
The trend of mobile malwares and effective detection techniques
by: Abdul Aziz, Normaziah, et al.
Published: (2015) -
Techniques for analysing android malware
by: Adebayo, Olawale Surajudeen, et al.
Published: (2014) -
Analysis of THUG: a low-interaction client honeypot to identify malicious websites and malwares
by: Zulkurnain, Nurul Fariza, et al.
Published: (2018)