Automated Generation of Colluding Apps For Experimental Research. / Blasco Alis, Jorge; Chen, Thomas M.

In: Journal of Computer Virology and Hacking Techniques, 06.04.2017, p. 1-12.

Research output: Contribution to journalArticle

E-pub ahead of print

Abstract

Colluding apps bypass the security measures enforced by sandboxed operating systems such as Android. App collusion can be a real threat in cloud environments as well. Research in detecting and protecting against app collusion requires a variety of colluding apps for experimentation.
Presently the number of (real or manually crafted) apps available to researchers is very limited. In this paper we propose a system called Application Collusion Engine (ACE) to automatically generate combinations of colluding and non-colluding Android apps to help researchers fairly evaluate different collusion detection and protection methods.
Our initial implementation includes a variety of components that enable the system to create more than 5,000 different colluding and non-colluding app sets. ACE can be extended with more functional components to create even more colluding apps. To show the usefulness of our system, we have applied different risk evaluation and collusion detection methods to the created set of colluding apps.
Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalJournal of Computer Virology and Hacking Techniques
Early online date6 Apr 2017
DOIs
StateE-pub ahead of print - 6 Apr 2017
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 27876352