NDLI: DRACO: DRoid analyst combo an android malware analysis framework

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DRACO: DRoid analyst combo an android malware analysis framework

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DRACO: DRoid analyst combo an android malware analysis framework

Content Provider	ACM Digital Library
Author	Gaur, Manoj Singh Anikeev, Maxim Gupta, Rishabh Laxmi, Vijay Zemmari, Akka Bhandari, Shweta
Abstract	Android being the most popular open source mobile operating system, attracts a plethora of app developers. Millions of applications are developed for Android platform with a great extent of behavioral diversities and are available on Play Store as well as on many third party app stores. Due to its open nature, in the past Android Platform has been targeted by many malware writers. The conventional way of signature-based detection methods for detecting malware on a device are no longer promising due to an exponential increase in the number of variants of the same application with different signatures. Moreover, they lack in dynamic analysis too. In this paper, we propose DRACO, which employs a two-phase detection technique that blends the synergy of both static and dynamic analysis. It has two modules, client module that is in the form an Android app and gets installed on mobile devices and a server module that runs on a server. DRACO also explains user about the features contributing to the maliciousness of analyzed app and generates scoring for that maliciousness. It does not require any root or super-user privileges. In an evaluation of 18,000 benign applications and 10,000 malware samples, DRACO performs better than several related existing approaches and detects 98.4% of the malware with few false alerts. On ten popular smartphones, the method requires an average of 6 seconds for on device analysis and 90 seconds on server analysis.
Starting Page	283
Ending Page	289
Page Count	7
File Format	PDF
ISBN	9781450334532
DOI	10.1145/2799979.2800003
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-09-08
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Android malware analysis Machine learning
Content Type	Text
Resource Type	Article

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