A Function-Centric Risk Assessment Approach for Android Applications

Different risk evaluation approaches exist to protect users from potentially malicious apps. However, while assessing risks, the existing approaches ignore users' functional needs, and that app funGuojun Wangctions help their developers compete in the marketplace. In this paper, we propose a fu...

Full description

Saved in:
Bibliographic Details
Main Authors: Li, Min, Elahi, Haroon, Peng, Tao, Qi, Fang, Wang, Guojun
Format: Conference Proceeding
Language:English
Subjects:
Android (operating system)
Android apps
App marketplace
App risks
app store
app-category
competitive apps
competitive functions
Data privacy
Force
function-centric risk assessment approach
funGuojun Wangctions
learning (artificial intelligence)
Machine learning
mobile computing
Operations research
Permission clustering
potentially malicious apps
Privacy
risk analysis
Risk assessment
risk evaluation
Risk management
safe apps
Security
security of data
smart phones
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Different risk evaluation approaches exist to protect users from potentially malicious apps. However, while assessing risks, the existing approaches ignore users' functional needs, and that app funGuojun Wangctions help their developers compete in the marketplace. In this paper, we propose a function-centric risk assessment approach for Android apps. The proposed approach combines operation research and machine learning methods to calculate the risks of an app and offers five competitive apps in the same app-category. We evaluate the proposed approach using 1,377 apps in sixteen app-categories, obtained from the most popular app store of 2019 in China, "Ying Yong Bao." The experimental evaluation demonstrates the feasibility of the proposed approach. This approach can help users select safe apps in the marketplace that offer competitive functions.
ISSN:2324-9013
DOI:10.1109/TrustCom50675.2020.00159