Inference attack in android activity based on program fingerprint

Yang, L; Wei, T; Ma, J; Yu, S; Yang, C

Inference attack in android activity based on program fingerprint

Yang, L Wei, T Ma, J Yu, S

Yang, C

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Publication Type:: Conference Proceeding
Citation:: 2018 IEEE Conference on Communications and Network Security, CNS 2018, 2018
Issue Date:: 2018-08-10

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Field	Value	Language
dc.contributor.author	Yang, L	en_US
dc.contributor.author	Wei, T	en_US
dc.contributor.author	Ma, J	en_US
dc.contributor.author	Yu, S https://orcid.org/0000-0003-4485-6743	en_US
dc.contributor.author	Yang, C	en_US
dc.date.issued	2018-08-10	en_US
dc.identifier.citation	2018 IEEE Conference on Communications and Network Security, CNS 2018, 2018	en_US
dc.identifier.isbn	9781538645864	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133543
dc.description.abstract	© 2018 IEEE. Private breach has always been an important threat to mobile security. Recent studies show that an attacker can infer user 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 the most of Activity transition and Activity interface process. Moreover, we propose a protection scheme which can effectively resist side-channel attacks.	en_US
dc.relation.ispartof	2018 IEEE Conference on Communications and Network Security, CNS 2018	en_US
dc.relation.isbasedon	10.1109/CNS.2018.8433169	en_US
dc.title	Inference attack in android activity based on program fingerprint	en_US
dc.type	Conference Proceeding
utslib.for	0805 Distributed Computing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2018 IEEE. Private breach has always been an important threat to mobile security. Recent studies show that an attacker can infer user 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 the most of Activity transition and Activity interface process. Moreover, we propose a protection scheme which can effectively resist side-channel attacks.

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http://hdl.handle.net/10453/133543