Generating Accurate Rule Sets Without Global Optimization
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Data Mining Methods for Detection of New Malicious Executables
SP '01 Proceedings of the 2001 IEEE Symposium on Security and Privacy
Intrusion detection techniques for mobile wireless networks
Wireless Networks
A cooperative intrusion detection system for ad hoc networks
Proceedings of the 1st ACM workshop on Security of ad hoc and sensor networks
Mobile Phones as Computing Devices: The Viruses are Coming!
IEEE Pervasive Computing
Towards an Intrusion Detection System for Battery Exhaustion Attacks on Mobile Computing Devices
PERCOMW '05 Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications Workshops
A General Cooperative Intrusion Detection Architecture for MANETs
IWIA '05 Proceedings of the Third IEEE International Workshop on Information Assurance
Host-Based Intrusion Detection for Advanced Mobile Devices
AINA '06 Proceedings of the 20th International Conference on Advanced Information Networking and Applications - Volume 02
Static disassembly of obfuscated binaries
SSYM'04 Proceedings of the 13th conference on USENIX Security Symposium - Volume 13
Mobile Device Profiling and Intrusion Detection Using Smart Batteries
HICSS '08 Proceedings of the Proceedings of the 41st Annual Hawaii International Conference on System Sciences
Monitoring smartphones for anomaly detection
Proceedings of the 1st international conference on MOBILe Wireless MiddleWARE, Operating Systems, and Applications
Behavioral detection of malware on mobile handsets
Proceedings of the 6th international conference on Mobile systems, applications, and services
Detecting energy-greedy anomalies and mobile malware variants
Proceedings of the 6th international conference on Mobile systems, applications, and services
A Virus Prevention Model Based on Static Analysis and Data Mining Methods
CITWORKSHOPS '08 Proceedings of the 2008 IEEE 8th International Conference on Computer and Information Technology Workshops
CloudAV: N-version antivirus in the network cloud
SS'08 Proceedings of the 17th conference on Security symposium
IDAMN: an intrusion detection architecture for mobile networks
IEEE Journal on Selected Areas in Communications
Crowdroid: behavior-based malware detection system for Android
Proceedings of the 1st ACM workshop on Security and privacy in smartphones and mobile devices
RGBDroid: a novel response-based approach to android privilege escalation attacks
LEET'12 Proceedings of the 5th USENIX conference on Large-Scale Exploits and Emergent Threats
Detecting money-stealing apps in alternative Android markets
Proceedings of the 2012 ACM conference on Computer and communications security
MADAM: a multi-level anomaly detector for android malware
MMM-ACNS'12 Proceedings of the 6th international conference on Mathematical Methods, Models and Architectures for Computer Network Security: computer network security
Sweetening android lemon markets: measuring and combating malware in application marketplaces
Proceedings of the third ACM conference on Data and application security and privacy
Tap-Wave-Rub: lightweight malware prevention for smartphones using intuitive human gestures
Proceedings of the sixth ACM conference on Security and privacy in wireless and mobile networks
Mobile-sandbox: having a deeper look into android applications
Proceedings of the 28th Annual ACM Symposium on Applied Computing
ADAM: an automatic and extensible platform to stress test android anti-virus systems
DIMVA'12 Proceedings of the 9th international conference on Detection of Intrusions and Malware, and Vulnerability Assessment
MeadDroid: detecting monetary theft attacks in android by DVM monitoring
ICISC'12 Proceedings of the 15th international conference on Information Security and Cryptology
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Smartphones are getting increasingly popular and several malwares appeared targeting these devices. General countermeasures to smartphone malwares are currently limited to signature-based antivirus scanners which efficiently detect known malwares, but they have serious shortcomings with new and unknown malwares creating a window of opportunity for attackers. As smartphones become host for sensitive data and applications, extended malware detection mechanisms are necessary complying with the corresponding resource constraints. The contribution of this paper is twofold. First, we perform static analysis on the executables to extract their function calls in Android environment using the command readelf. Function call lists are compared with malware executables for classifying them with PART, Prism and Nearest Neighbor Algorithms. Second, we present a collaborative malware detection approach to extend these results. Corresponding simulation results are presented.