Title :
Research of Intrusion Detection System on Android
Author :
Fangfang Yuan ; Lidong Zhai ; Yanan Cao ; Li Guo
Author_Institution :
Inst. of Inf. Eng., Beijing, China
fDate :
June 28 2013-July 3 2013
Abstract :
In this paper, we proposed an intrusion detection system for detecting anomaly on Android smartphones. The intrusion detection system continuously monitors and collects the information of smartphone under normal conditions and attack state. It extracts various features obtained from the Android system, such as the network traffic of smartphones, battery consumption, CPU usage, the amount of running processes and so on. Then, it applies Bayes Classifying Algorithm to determine whether there is an invasion. In order to further analyze the Android system abnormalities and locate malicious software, along with system state monitoring the intrusion detection system monitors the process and network flow of the smartphone. Finally, experiments on the system which was designed in this paper have been carried out. Empirical results suggest that the proposed intrusion detection system is effective in detecting anomaly on Android smartphones.
Keywords :
Bayes methods; feature extraction; mobile computing; pattern classification; security of data; smart phones; system monitoring; Android smartphone; Android system abnormalities; Bayes classifying algorithm; CPU usage; anomaly detection; attack state; battery consumption; continuous information monitoring; feature extraction; information collection; intrusion detection system monitor; invasion; malicious software location; network flow; network traffic; running processes; system state monitoring; Data mining; Feature extraction; Intrusion detection; Malware; Monitoring; Smart phones; Smartphones; Monitoring; Android; Security;
Conference_Titel :
Services (SERVICES), 2013 IEEE Ninth World Congress on
Conference_Location :
Santa Clara, CA
Print_ISBN :
978-0-7695-5024-4
DOI :
10.1109/SERVICES.2013.77