NDLI: Detection of Android Malicious Apps Based on the Sensitive Behaviors

Content Provider	IEEE Xplore Digital Library
Author	Daiyong Quan Lidong Zhai Fan Yang Peng Wang
Copyright Year	2014
Description	Author affiliation: Inst. of Inf. Eng., Beijing, China (Daiyong Quan; Lidong Zhai; Fan Yang; Peng Wang)
Abstract	The number of malicious applications (apps) targeting the Android system has exploded in recent years. The evolution of malware makes it difficult to detect for static analysis tools. Various behavior-based malware detection techniques to mitigate this problem have been proposed. The drawbacks of the existing approaches are: the behavior features extracted from a single source lead to the low detection accuracy and the detection process is too complex. Especially it is unsuitable for smart phones with limited computing power. In this paper, we extract sensitive behavior features from three sources: API calls, native code dynamic execution, and system calls. We propose a sensitive behavior feature vector for representation multi-source behavior features uniformly. Our sensitive behavior representation is able to automatically describe the low-level OS-specific behaviors and high-level application-specific behaviors of an Android malware. Based on the unified behavior feature representation, w e provide a light weight decision function to differentiate a given application benign or malicious. We tested the effectiveness of our approach against real malware and the results of our experiments show that its detection accuracy up to 96% with acceptable performance overhead. For a given threshold t (t=9), we can detect the advanced malware family effectively.
Starting Page	877
Ending Page	883
File Size	402010
Page Count	7
File Format	PDF
ISBN	9781479965137
DOI	10.1109/TrustCom.2014.115
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Humanoid robots Feature extraction Malware Vectors Sensitive behavior feature vector Androids Malware detection Smart phones Monitoring Android
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in