Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/132211
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Type: Conference paper
Title: An automated assessment of android clipboards
Author: Wei, W.
Sun, R.
Xue, M.
Ranasinghe, D.
Citation: Proceedings / IEEE International Conference, Automated Software Engineering ; sponsored by IEEE Computer Society, NASA Ames Research Center, in cooperation with AAAI, ACM SIGART and SIGSOFT. IEEE International Automated Software Enginee..., 2020, pp.1249-1251
Publisher: IEEE/ACM
Publisher Place: online
Issue Date: 2020
Series/Report no.: IEEE ACM International Conference on Automated Software Engineering
ISBN: 9781450367684
ISSN: 1938-4300
2643-1572
Conference Name: IEEE/ACM International Conference on Automated Software Engineering (ASE) (21 Sep 2020 - 25 Sep 2020 : virtual online)
Statement of
Responsibility: 
Wei Wang, Ruoxi Sun, Minhui Xue, Damith C. Ranasinghe
Abstract: Since the new privacy feature in iOS enabling users to acknowledge which app is reading or writing to his or her clipboard through prompting notifications was updated, a plethora of top apps have been reported to frequently access the clipboard without user consent. However, the lack of monitoring and control of Android application’s access to the clipboard data leave Android users blind to their potential to leak private information from Android clipboards, raising severe security and privacy concerns. In this preliminary work, we envisage and investigate an approach to (i) dynamically detect clipboard access behaviour, and (ii) determine privacy leaks via static data flow analysis, in which we enhance the results of taint analysis with call graph concatenation to enable leakage source backtracking. Our preliminary results indicate that the proposed method can expose clipboard data leakage as substantiated by our discovery of a popular app, i.e., Sogou Input, directly monitoring and transferring user data in a clipboard to backend servers.
Rights: © 2020 Association for Computing Machinery.
DOI: 10.1145/3324884.3418905
Published version: https://dl.acm.org/doi/proceedings/10.1145/3324884
Appears in Collections:Computer Science publications

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