Detecting and Classifying Android PUAs by Similarity of DNS queries

Mitsuhiro Hatada, Tatsuya Mori

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

This work develops a method of detecting and classifying 'potentially unwanted applications' (PUAs) such as adware or remote monitoring tools. Our approach leverages DNS queries made by apps. Using a large sample of Android apps from third-party marketplaces, we first reveal that DNS queries can provide useful information for the detection and classification of PUAs. Next, we show that existing DNS blacklists are ineffective to perform these tasks. Finally, we demonstrate that our methodology performed with high accuracy.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE 41st Annual Computer Software and Applications Conference Workshops, COMPSAC 2017
EditorsClaudio Demartini, Ji-Jiang Yang, Sheikh Iqbal Ahamed, Thomas Conte, Toyokazu Akiyama, Sorel Reisman, Hiroki Takakura, Kamrul Hasan, William Claycomb, Motonori Nakamura, Edmundo Tovar, Zhiyong Zhang, Ling Liu, Chung-Horng Lung, Stelvio Cimato
PublisherIEEE Computer Society
Pages590-595
Number of pages6
ISBN (Electronic)9781538603673
DOIs
Publication statusPublished - 2017 Sept 7
Event41st IEEE Annual Computer Software and Applications Conference Workshops, COMPSAC 2017 - Torino, Italy
Duration: 2017 Jul 42017 Jul 8

Publication series

NameProceedings - International Computer Software and Applications Conference
Volume2
ISSN (Print)0730-3157

Other

Other41st IEEE Annual Computer Software and Applications Conference Workshops, COMPSAC 2017
Country/TerritoryItaly
CityTorino
Period17/7/417/7/8

ASJC Scopus subject areas

  • Software
  • Computer Science Applications

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