Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications

DRFuzzer: Detector of Android APP inter-component vulnerability

Authors
Hongji Song, Hua Zhang
Corresponding Author
Hongji Song
Available Online November 2016.
DOI
10.2991/aiea-16.2016.63How to use a DOI?
Keywords
Fuzzing; custom Android OS; vulnerability; inter-component.
Abstract

In recent years, the Android system developed rapidly. It has become the leader of the smart phone operating system. The research of Android security mechanisms is significant. If an Android application could not protect its private components well in the process of inter-application communication, there would exist exposed component vulnerabilities. The current vulnerability detection methods cannot identify such vulnerabilities accurately. To solve this problem, we propose a new method combines Fuzzing with custom Android OS and design a vulnerability mining tool named DRFuzzer. Experimental results show that the tool can effective and comprehensive discover vulnerabilities in communication between components, and provide possibility for solving some deep problems.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
Series
Advances in Computer Science Research
Publication Date
November 2016
ISBN
10.2991/aiea-16.2016.63
ISSN
2352-538X
DOI
10.2991/aiea-16.2016.63How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Hongji Song
AU  - Hua Zhang
PY  - 2016/11
DA  - 2016/11
TI  - DRFuzzer: Detector of Android APP inter-component vulnerability
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
PB  - Atlantis Press
SP  - 353
EP  - 357
SN  - 2352-538X
UR  - https://doi.org/10.2991/aiea-16.2016.63
DO  - 10.2991/aiea-16.2016.63
ID  - Song2016/11
ER  -