Regular Papers

Session I: Mobile Applications

A Scalable and Accurate Feature Representation Method for Identifying Malicious Mobile Applications
Bo Sun, Tao Ban, Shun-Chieh Chang, Yeali S. Sun, Takeshi Takahashi and Daisuke Inoue
National Institute of Information and Communications Technology, Japan
Institute for Information Industry, Taiwan
National Taiwan University, Taiwan

Machine Learning for Improving Mobile User Satisfaction
Ismat Chaib Draa, Smail Niar, Fabien Bouquillon and Emmanuelle Grislin-Le Strugeon
Universite Polytechnique des Hauts-de-France, France

MoCA: A Novel Privacy-preserving Contextual Advertising Platform on Mobile Devices
Jung-Hyun Lee, Woo-Jong Ryu, Kang-Min Kim and SangKeun Lee
Korea University, Korea

A Multi-Objective Indoor Localization Service for Smartphones
Andreas Konstantinidis, Aphrodite Demetriades and Savvas Pericleous
Frederick University, Cyprus

Acousess: Smartphone-based Logger to Assess Acoustical Conditions
Takahiro Miura, Mari Ueda, Masaaki Hiroe and Ken-ichiro Yabu
National Institute of Advanced Industrial Science and Technology, Japan
University of Tokyo, Japan
Tsukuba University of Technology, Japan
Kanagawa Institute of Technology, Japan
Kobayashi Institute of Physical Research, Japan

Poster Paper

Extended Sammon Projection and Wavelet Kernel Extreme Learning Machine for Gait-based Legitimate User Identification
Muhammad Ahmad, Adil Mehmood Khan, Manuel Mazzara, Salvatore Distefano, Amjad Ali and Ali Tufail
Innopolis University, Russia
University of Messina, Italy
Korea University, Korea
Islamic University of Medina, Saudi Arabia