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Inference attack in Android Activity based on program fingerprint

delete2019-02-01
delete9
PRE
AI
L
Li Yang *
W
Wei Teng
S
Shui Yu
马
马建峰 (Jianfeng Ma)
DOI:10.1016/j.jnca.2018.12.007delete
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摘要

摘要

En 中文
Private breach has always been an important threat to mobile security. Recent studies show that an attacker can infer users' private information through side channels, such as the use of runtime memory and network usage. For side-channel attacks, malicious applications generally run parallel in the background with a foreground application and stealthily collect side-channel information. In this paper, we analyze the relationship between memory changes and Activity transition, then use side-channel information to label an Activity and build an Activity signature database. We show how to use the runtime memory exposure to infer the Activity transition of the current application and use other side channels to infer its Activity interface. We demonstrate the effectiveness of the attacks with 5 popular applications that contain user sensitive information, and successfully inferred most of the Activity transition and Activity interface process. Moreover, we propose a protection scheme which can effectively resist side-channel attacks.
Keyword:
Android security
Side-channel attack
Activity inference
Program fingerprint
Protection
AI总结

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期刊

Journal of Network and Computer Applications 封面图
Journal of Network and Computer Applications
IF:
8
论文数:
3.6K
被引数:
1.1W

机构

X
Xidian University
学者数:
2.4W
论文数: 1.9W
被引数: 9.7K
D
Deakin University
学者数:
2.0W
论文数: 2.1W
被引数: 2.8W
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