The rise of “malware”: Bibliometric analysis of malware study

MF Ab Razak, NB Anuar, R Salleh, A Firdaus - Journal of Network and …, 2016 - Elsevier
Malicious software (malware) is a computer program designed to create harmful and
undesirable effects. It considered as one of the many dangerous threats for Internet users …

Machine learning classification model for network based intrusion detection system

S Kumar, A Viinikainen… - 2016 11th international …, 2016 - ieeexplore.ieee.org
With an enormous increase in number of mobile users, mobile threats are also growing
rapidly. Mobile malwares can lead to several cybersecurity threats ie stealing sensitive …

An integrated static detection and analysis framework for android

J Song, C Han, K Wang, J Zhao, R Ranjan… - Pervasive and Mobile …, 2016 - Elsevier
The security and privacy issues of android system have attracted a lot of attention from both
industry and academia in recent years. Static detection is one typical method to analyze …

Machine learning classifiers for android malware analysis

CCU Lopez, AN Cadavid - 2016 IEEE Colombian Conference …, 2016 - ieeexplore.ieee.org
Android is an operating system which currently has over one billion active users for all their
mobile devices, with a market impact that is influencing an increase in the amount of …

Framework for malware analysis in Android

C Urcuqui-López, AN Cadavid - Sistemas y Telemática, 2016 - icesi.edu.co
Android is a open source operating system with more than a billion of users, including all
kind of devices (cell phones, TV, smart watch, etc). The amount of sensitive data “using” this …

More semantics more robust: Improving android malware classifiers

W Chen, D Aspinall, AD Gordon, C Sutton… - Proceedings of the 9th …, 2016 - dl.acm.org
Automatic malware classifiers often perform badly on the detection of new malware, ie, their
robustness is poor. We study the machine-learning-based mobile malware classifiers and …

[图书][B] Relationship between effective application of machine learning and malware detection: A quantitative study

KW Enfinger - 2016 - search.proquest.com
The number of malicious files present in the public domain continues to rise at a substantial
rate. Current anti-malware software utilizes a signature-based method to detect the …

[PDF][PDF] Módulo de machine learning para detección de malware en Android

CCU López - researchgate.net
Android es un sistema operativo de código abierto con más de mil millones de usuarios
activos para todos sus dispositivos; durante los últimos años este y otros eventos han …

Framework para analisis de software malicioso en Android

CCU López, AN Cadavid - Sistemas & Telematica, 2016 - go.gale.com
Android es un sistema operativo de código abierto con más de mil millones de usuarios
activos para todos sus dispositivos (móviles, televisión, relojes inteligentes, entre otros). La …

[PDF][PDF] Dark of the social networks, Journal of Network and Computer Applications

KS Adewole, NB Anuar, A Kamsin, KD Varathan… - 2016 - academia.edu
Over the last few years, online social networks (OSNs), such as Facebook, Twitter and
Tuenti, have experienced exponential growth in both profile registrations and social …