Paper Info
Title
MBotCS: A Mobile Botnet Detection System Based on Machine Learning.
Abstract
As the use of mobile devices spreads dramatically, hackers have started making use of mobile botnets to steal user information or perform other malicious attacks. To address this problem, in this paper we propose a mobile botnet detection system, called MBotCS. MBotCS can detect mobile device traffic indicative of the presence of a mobile botnet based on prior training using machine learning techniques. Our approach has been evaluated using real mobile device traffic captured from Android mobile devices, running normal apps and mobile botnets. In the evaluation, we investigated the use of 5 machine learning classifier algorithms and a group of machine learning box algorithms with different validation schemes. We have also evaluated the effect of our approach with respect to its effect on the overall performance and battery consumption of mobile devices.
Year
Venue
Field
2015
CRiSIS
Mobile computing,Computer science,Botnet,Computer security,Computer network,Artificial intelligence,Mobile Web,Learning classifier system,Mobile technology,Mobile search,Android (operating system),Mobile device,Machine learning
DocType
Citations 
PageRank 
Conference
1
0.35
References 
Authors
16
2
Name
Order
Citations
PageRank
Xin Meng111012.27
George Spanoudakis21057108.40