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Functionality-based mobile application recommendation system with security and privacy awareness

delete2020-10-01
delete5
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OA
AI
T
Thiago Rocha *
E
Eduardo Souto
K
Khalil El‐Khatib
DOI:10.1016/j.cose.2020.101972delete
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Abstract

Abstract

En 中文
Nowadays, there are a variety of mobile device applications to execute tasks, such as paying bills and ordering food. However, some apps (malicious) claim that they perform a certain task just to lure users to damage their devices and/or execute malicious activities such as leaking sensitive information. Because of that, users need a way to choose an app that is safe and meets their needs. Recommendation systems are currently being used to choose apps, but most approaches do not evaluate security and privacy, and when they do, only permissions are considered. In this context, this work presents a novel system to evaluate and suggest apps. The main contributions are the addition of a security layer, the evaluation of the metrics inside a functionality context and a mapping between permissions and API calls raising user confidence and understanding. (c) 2020 Elsevier Ltd. All rights reserved.
Keywords:
Security
Privacy
Recommendation
Malware
Android
AI Summary

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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

C
Computers and Security
IF:
5.4
Papers:
4.6K
Citations:
1.4W

Organization

U
universidade federal de amazonas
Scholars:
2.8K
Papers: 1.6K
Citations: 1