Android Malware Characterization Using Metadata and Machine Learning Techniques Articles uri icon

publication date

  • July 2018

start page

  • 1

end page

  • 11


  • 2018

International Standard Serial Number (ISSN)

  • 1939-0114

Electronic International Standard Serial Number (EISSN)

  • 1939-0122


  • Android malware has emerged as a consequence of the increasing popularity of smartphones and tablets. While most previous work focuses on inherent characteristics of Android apps to detect malware, this study analyses indirect features and metadata to identify patterns in malware applications. Our experiments show the following: (1) the permissions used by an application offer only moderate performance results; (2) other features publicly available at Android markets are more relevant in detecting malware, such as the application developer and certificate issuer; and (3) compact and efficient classifiers can be constructed for the early detection of malware applications prior to code inspection or sandboxing.


  • Telecommunications