NDLI: MARVIN: Efficient and Comprehensive Mobile App Classification through Static and Dynamic Analysis

Content Provider	IEEE Xplore Digital Library
Author	Lindorfer, M. Neugschwandtner, M. Platzer, C.
Copyright Year	2015
Description	Author affiliation: SBA Res., Vienna, Austria (Lindorfer, M.) \|\| Int. Secure Syst. Lab., Vienna Univ. of Technol., Vienna, Austria (Neugschwandtner, M.; Platzer, C.)
Abstract	Android dominates the smartphone operating system market and consequently has attracted the attention of malware authors and researchers alike. Despite the considerable number of proposed malware analysis systems, comprehensive and practical malware analysis solutions are scarce and often short-lived. Systems relying on static analysis alone struggle with increasingly popular obfuscation and dynamic code loading techniques, while purely dynamic analysis systems are prone to analysis evasion. We present MARVIN, a system that combines static with dynamic analysis and which leverages machine learning techniques to assess the risk associated with unknown Android apps in the form of a malice score. MARVIN performs static and dynamic analysis, both off-device, to represent properties and behavioral aspects of an app through a rich and comprehensive feature set. In our evaluation on the largest Android malware classification data set to date, comprised of over 135,000 Android apps and 15,000 malware samples, MARVIN correctly classifies 98.24% of malicious apps with less than 0.04% false positives. We further estimate the necessary retraining interval to maintain the detection performance and demonstrate the long-term practicality of our approach.
Starting Page	422
Ending Page	433
File Size	931114
Page Count	12
File Format	PDF
ISSN	07303157
e-ISBN	9781467365642
DOI	10.1109/COMPSAC.2015.103
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-01
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Malware Feature extraction Androids Humanoid robots Mobile communication Google Training classification mobile security malware analysis
Content Type	Text
Resource Type	Article
Subject	Computer Science Applications Software

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
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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