RT info:eu-repo/semantics/article
T1 Key features for the characterization of Android malware families
A1 Sedano, Javier
A1 González González, Silvia .
A1 Chira, Camelia
A1 Herrero Cosío, Álvaro
A1 Corchado, Emilio
A1 Villar, José Ramón
K1 Feature selection
K1 Evolutionary computation
K1 Max-relevance min-redundancy criteria
K1 Information correlation coefficient
K1 Android
K1 Malware
K1 Informática
K1 Computer science
AB In recent years, mobile devices such as smartphones, tablets and wearables have become the new paradigm of user–computerinteraction. The increasing use and adoption of such devices is also leading to an increased number of potential security risks.The spread of mobile malware, particularly on popular and open platforms such as Android, has become a major concern.This paper focuses on the bad-intentioned Android apps by addressing the problem of selecting the key features of suchsoftware that support the characterization of such malware. The accurate detection and characterization of this software isstill an open challenge, mainly due to its ever-changing nature and the open distribution channels of Android apps. Maximumrelevance minimum redundancy and evolutionary algorithms guided by information correlation measures have been appliedfor feature selection on the well-known Android Malware Genome (Malgenome) dataset, attaining interesting results on themost informative features for the characterization of representative families of existing Android malware.
PB Oxford University Press
SN 1367-0751
YR 2017
FD 2017-02
LK http://hdl.handle.net/10259/7265
UL http://hdl.handle.net/10259/7265
LA eng
NO This research has been partially supported through the project of the Spanish Ministry of Economy and Competitiveness RTC-2014-3059-4. The authors would also like to thank the BIO/BU01/15 and the Spanish Ministry of Science and Innovation PID 560300-2009-11.
DS Repositorio Institucional de la Universidad de Burgos
RD 23-nov-2024