Attention: there is an inconsistency between android permissions and application metadata!


Alecakir H., Can B., Sen S.

INTERNATIONAL JOURNAL OF INFORMATION SECURITY, vol.20, no.6, pp.797-815, 2021 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 20 Issue: 6
  • Publication Date: 2021
  • Doi Number: 10.1007/s10207-020-00536-1
  • Journal Name: INTERNATIONAL JOURNAL OF INFORMATION SECURITY
  • Journal Indexes: Science Citation Index Expanded, Scopus, Academic Search Premier, FRANCIS, ABI/INFORM, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Compendex, Computer & Applied Sciences, Criminal Justice Abstracts, INSPEC
  • Page Numbers: pp.797-815
  • Keywords: Android, Security, Description-to-permission fidelity, Natural language processing, Recurrent neural networks, Attention mechanism

Abstract

Since mobile applications make our lives easier, there is a large number of mobile applications customized for our needs in the application markets. While the application markets provide us a platform for downloading applications, it is also used by malware developers in order to distribute their malicious applications. In Android, permissions are used to prevent users from installing applications that might violate the users' privacy by raising their awareness. From the privacy and security point of view, if the functionality of applications is given in sufficient detail in their descriptions, then the requirement of requested permissions could be well-understood. This is defined as description-to-permission fidelity in the literature. In this study, we propose two novel models that address the inconsistencies between the application descriptions and the requested permissions. The proposed models are based on the current state-of-art neural architectures called attention mechanisms. Here, we aim to find the permission statement words or sentences in app descriptions by using the attention mechanism along with recurrent neural networks. The lack of such permission statements in application descriptions creates a suspicion. Hence, the proposed approach could assist in static analysis techniques in order to find suspicious apps and to prioritize apps for more resource intensive analysis techniques. The experimental results show that the proposed approach achieves high accuracy.