Abstract
As Android is becoming more and more prevalent in modern devices, malware targeting Android systems is significantly increasing. New generation of malware has great diversity and uses more sophisticated techniques to hide traces and fool traditional detection methods. On the other hand, many researchers have proposed various techniques and tools for detecting and classifying Android malware. The evaluation of most of these tools is based on closed or obsolete datasets, and likely the reported performance metrics are biased towards specific features or categories of malware. In this paper, we intensively evaluate the performance of an existing open-source tool, known as Dr-Droid, and benchmark its performance against several online standard malware detection engines freely accessible through VirusTotal website. The dataset has been recently revealed and covers a large number of Android malware categories and families.
Original language | English |
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Title of host publication | 2019 2nd IEEE Middle East and North Africa COMMunications Conference, MENACOMM 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781728136875 |
DOIs | |
State | Published - Nov 2019 |
Publication series
Name | 2019 2nd IEEE Middle East and North Africa COMMunications Conference, MENACOMM 2019 |
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Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- Android platform
- Mobile security
- dynamic analysis
- malware detection
- open-source tools
- static analysis
ASJC Scopus subject areas
- Information Systems and Management
- Safety, Risk, Reliability and Quality
- Signal Processing
- Computer Networks and Communications
- Hardware and Architecture