RT info:eu-repo/semantics/article
T1 Gaining deep knowledge of Android malware families through dimensionality reduction techniques
A1 Vega Vega, Rafael Alejandro
A1 Quintián, Héctor
A1 Calvo-Rolle, José Luis
A1 Herrero Cosío, Álvaro
A1 Corchado, Emilio
K1 Android malware
K1 Malware families
K1 Dimensionality reduction
K1 Artificial neural networks
K1 Informática
K1 Computer science
AB This research proposes the analysis and subsequent characterisation of Android malware families by means of lowdimensional visualisations using dimensional reduction techniques. The well-known Malgenome data set, coming fromthe Android Malware Genome Project, has been thoroughly analysed through the following six dimensionality reductiontechniques: Principal Component Analysis, Maximum Likelihood Hebbian Learning, Cooperative Maximum LikelihoodHebbian Learning, Curvilinear Component Analysis, Isomap and Self Organizing Map. Results obtained enable a clear visualanalysis of the structure of this high-dimensionality data set, letting us gain deep knowledge about the nature of such Androidmalware families. Interesting conclusions are obtained from the real-life data set under analysis.
PB Oxford University Press
SN 1367-0751
YR 2019
FD 2019-04
LK http://hdl.handle.net/10259/7252
UL http://hdl.handle.net/10259/7252
LA eng
DS Repositorio Institucional de la Universidad de Burgos
RD 23-nov-2024