TY - JOUR
T1 - Detecting injected behaviors in HTML5-based Android applications
AU - Mao, Jian
AU - Wang, Ruilong
AU - Chen, Yue
AU - Jia, Yaoqi
N1 - Publisher Copyright:
© 2016 - IOS Press and the authors. All rights reserved.
PY - 2016/2/10
Y1 - 2016/2/10
N2 - HTML5-based mobile applications (or apps) are built by using standard web technologies such as HTML5, JavaScript and CSS. Due to their cross-platform support, HTML5-based mobile apps are getting more and more popular. However, similar to traditional web apps, they are often vulnerable to script-injection attacks. It results in new threats to code integrity and data privacy. Compared to traditional web apps, HTML5-based mobile apps have more possible channels to inject code, e.g., contacts, SMS, files, NFC, and cameras. Even worse, the injected scripts may gain much more powerful privileges from the mobile apps than those in the traditional web apps. In this paper, we propose an approach to detect injected behaviors in HTML5-based Android apps. Our approach monitors the execution of apps, and generates behavior state machines to describe the apps' runtime behaviors based on the execution contexts of apps. Once code injection happens, the injected behaviors will be detected based on deviation from the behavior state machine of the original app. We prototyped our approach and evaluated its effectiveness using existing code injection examples. The result demonstrates that the proposed method is effective in code injection detection for real-world HTML5-based Android apps.
AB - HTML5-based mobile applications (or apps) are built by using standard web technologies such as HTML5, JavaScript and CSS. Due to their cross-platform support, HTML5-based mobile apps are getting more and more popular. However, similar to traditional web apps, they are often vulnerable to script-injection attacks. It results in new threats to code integrity and data privacy. Compared to traditional web apps, HTML5-based mobile apps have more possible channels to inject code, e.g., contacts, SMS, files, NFC, and cameras. Even worse, the injected scripts may gain much more powerful privileges from the mobile apps than those in the traditional web apps. In this paper, we propose an approach to detect injected behaviors in HTML5-based Android apps. Our approach monitors the execution of apps, and generates behavior state machines to describe the apps' runtime behaviors based on the execution contexts of apps. Once code injection happens, the injected behaviors will be detected based on deviation from the behavior state machine of the original app. We prototyped our approach and evaluated its effectiveness using existing code injection examples. The result demonstrates that the proposed method is effective in code injection detection for real-world HTML5-based Android apps.
KW - Android security
KW - HTML5 apps
KW - detection
KW - injected behaviors
UR - https://www.scopus.com/pages/publications/84958975848
U2 - 10.3233/JHS-160534
DO - 10.3233/JHS-160534
M3 - 文章
AN - SCOPUS:84958975848
SN - 0926-6801
VL - 22
SP - 15
EP - 34
JO - Journal of High Speed Networks
JF - Journal of High Speed Networks
IS - 1
ER -