The Android malware detection systems between hope and reality
Open Access
- 29 August 2019
- journal article
- review article
- Published by Springer Nature in SN Applied Sciences
- Vol. 1 (9) , 1120
Abstract
No abstract availableKeywords
This publication has 198 references indexed in Scilit:
- Mining permission patterns for contrasting clean and malicious android applicationsFuture Generation Computer Systems, 2014
- Dendroid: A text mining approach to analyzing and classifying code structures in Android malware familiesExpert Systems with Applications, 2014
- Detecting mobile malware threats to homeland security through static analysisJournal of Network and Computer Applications, 2014
- Analysis of Bayesian classification‐based approaches for Android malware detectionIET Information Security, 2014
- A review of feature selection methods based on mutual informationNeural Computing and Applications, 2013
- ADAM: An Automatic and Extensible Platform to Stress Test Android Anti-virus Systems2013
- A Framework for Evaluating Mobile App Repackaging Detection AlgorithmsLecture Notes in Computer Science, 2013
- A taxonomy of self-modifying code for obfuscationComputers & Security, 2011
- Semantically rich application‐centric security in AndroidSecurity and Communication Networks, 2011
- CRePE: Context-Related Policy Enforcement for Android2011