Discovering inconsistencies between requested permissions and application metadata by using deep learning
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Issue Date
2021-12-31
Metadata
Show full item recordAbstract
Android gives us opportunity to extract meaningful information from metadata. From the security point of view, the missing important information in metadata of an application could be a sign of suspicious application, which could be directed for extensive analysis. Especially the usage of dangerous permissions is expected to be explained in app descriptions. The permission-to-description fidelity problem in the literature aims to discover such inconsistencies between the usage of permissions and descriptions. This study proposes a new method based on natural language processing and recurrent neural networks. The effect of user reviews on finding such inconsistencies is also investigated in addition to application descriptions. The experimental results show that high precision is obtained by the proposed solution, and the proposed method could be used for triage of Android applications.Citation
Alecakir, H., Kabukcu, M., Can, B. and Sen, S. (in press) Discovering inconsistencies between requested permissions and application metadata by using deep learning, ISCTurkey 2020.Publisher
ISCTurkeyAdditional Links
https://www.iscturkey.org/indexen.htmlType
Conference contributionLanguage
enDescription
This is an accepted manuscript of an article due to be published in the proceedings of ISCTurkey 2020. The accepted version of the publication may differ from the final published version.Collections
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc-nd/4.0/