arrow
Return

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
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

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.
Keywords:
Android security
Side-channel attack
Activity inference
Program fingerprint
Protection
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Journal of Network and Computer Applications cover
Journal of Network and Computer Applications
IF:
8
Papers:
3.6K
Citations:
1.1W

Organization

X
Xidian University
Scholars:
2.4W
Papers: 1.9W
Citations: 9.7K
D
Deakin University
Scholars:
2.0W
Papers: 2.1W
Citations: 2.8W
Cited Papers

Cited Papers

Modeling Malicious Activities in Cyber Space
err2015-11-01
err39
PREAI
errYu, Shui; Wang, Guojun; Zhou, Wanlei
errShare
errSave
The rise of keyloggers on smartphones: A survey and insight into motion-based tap inference attacks
err2016-01-01
err53
PREAI
errHussain, Muzammil; Al-Haiqi, Ahmed; Zaidan, A. A.; Zaidan, B. B.; Kiah, M. L. Mat; Anuar, Nor Badrul; Abdulnabi, Mohamed
errShare
errSave
errShare
errSave
A disproportionate role for the fornix and mammillary bodies in recall versus recognition memory
err2008-06-15
err0
PREAI
errDimitris Tsivilis; Seralynne D Vann; Christine Denby; Neil Roberts; Andrew R Mayes; Daniela Montaldi; John P Aggleton
errShare
errSave
no more