@inproceedings{9353314eed5c4ce1890ac3b3cba1a280,
title = "A function-level behavior model for anomalous behavior detection in hybrid mobile applications",
abstract = "Hybrid mobile applications (or apps) are based on web technologies, such as HTML5 and JavaScript, and run in a browser environment. They facilitate cross-platform development. However, the security issues of web technologies are inherited by hybrid mobile apps, where the injected code may execute with the system-level privilege. In this paper, we propose a behavior model to detect malicious behaviors in hybrid mobile apps. Our model uses function-level information to describe how an app's behaviors are activated. Furthermore, once script injection happens, the behaviors made by the injected code can be detected according to the deviation from the app's behavior model.",
keywords = "Behavior model, Code injection, Hybrid mobile application",
author = "Jian Mao and Ruilong Wang and Yue Chen and Yinhao Xiao and Yaoqi Jia and Zhenkai Liang",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2016 ; Conference date: 20-10-2016 Through 21-10-2016",
year = "2016",
month = jul,
day = "2",
doi = "10.1109/IIKI.2016.2",
language = "英语",
series = "Proceedings - 2016 International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "497--505",
booktitle = "Proceedings - 2016 International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2016",
address = "美国",
}