NDLI: On the automatic categorisation of android applications

Content Provider	IEEE Xplore Digital Library
Author	Sanz, B. Santos, I. Laorden, C. Ugarte-Pedrero, X. Bringas, P.G.
Copyright Year	2012
Description	Author affiliation: S3Lab, DeustoTech - Computing, Deusto Institute of Technology, Avenida de las Universidades 24, 48007, Bilbao, Spain (Sanz, B.; Santos, I.; Laorden, C.; Ugarte-Pedrero, X.; Bringas, P.G.)
Abstract	The presence of mobile devices has increased in our lives offering almost the same functionality as a personal computer. Android devices have appeared lately and, since then, the number of applications available for this operating system have increased exponentially. Google already has its Android Market where applications are offered and, as happens with every popular media, is prone to misuse. A malware writer may insert a malicious application into this market without being noticed. Indeed, there are already several cases of Android malware within the Android Market. Therefore, an approach that can automatically characterise the different types of applications can be helpful for both organising the Android Market and detecting fraudulent or malicious applications. In this paper, we propose a new method for categorising Android applications through machine-learning techniques. To represent each application, our method extracts different feature sets: (i) the frequency of occurrence of the printable strings, (ii) the different permissions of the application itself and (iii) the permissions of the application extracted from the Android Market. We evaluate this approach of automatically categorisation of Android applications and show that achieves a high performance.
Starting Page	149
Ending Page	153
File Size	1368209
Page Count	5
File Format	PDF
ISBN	9781457720703
e-ISBN	9781457720710
DOI	10.1109/CCNC.2012.6181075
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-01-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Humanoid robots Androids Feature extraction Malware Machine learning Learning systems Training
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
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