Authors: | Papamartzivanos D., Damopoulos D., Kambourakis G. |
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Title: | A cloud-based architecture to crowdsource mobile app privacy leaks |
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Conference: | The 18th Panhellenic Conference on Informatics (PCI 2014), special session on Security and Privacy Issues in the Cloud Computing Era |
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Editors: | |
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Ed: | No |
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Eds: | No |
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Pages: | 1-6 |
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To appear: | No |
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Month: | October |
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Year: | 2014 |
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Place: | Athens, Greece |
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Pubisher: | ACM press |
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Link: | http://dl.acm.org/citation.cfm?id=2645799 |
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File name: | sigproc-sp.pdf##^^&&758571482.pdf |
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Abstract: | Most would agree that modern app-markets have been flooded with applications that not only threaten the security of the OS uperficially, but also in their majority, trample on user’s privacy through the exposure of sensitive information not necessarily needed for their operation. In this context, the current work revolves around 3 key questions: Is there a way for the end-user to easily track - the many times - hidden privacy leaks occurring due to the way mobile apps operate? Can crowdsourcing provide the end-user with a quantitative assessment per app in terms of privacy exposure level? And if yes, in which way a cloud-based crowdsourcing mechanism can detect and alert for changes in the apps’ behavior? Motivated by the aforementioned questions, we design a cloud-based system that operates under a crowdsourcing logic, with the aim to provide i) a real-time privacy-flow tracking service, ii) a collaborative infrastructure for exchanging information related to apps’ privacy exposure level, and iii) potentially a behavior-driven detection mechanism in an effort to take advantage of the crowdsourcing data to its maximum efficasy. |