Automated generation of colluding apps for experimental research

Blasco, J. & Chen, T. (2018). Automated generation of colluding apps for experimental research. Journal of Computer Virology and Hacking Techniques, pp. 127-138. doi: 10.1007/s11416-017-0296-4

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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.

Publication Type: Article
Additional Information: © The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Departments: School of Mathematics, Computer Science & Engineering > Engineering
School of Mathematics, Computer Science & Engineering > Engineering > Electrical & Electronic Engineering
URI: http://openaccess.city.ac.uk/id/eprint/19489

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