Early detection of violating Mobile Apps: A data-driven predictive model approach
Mobile app stores are the key distributors of mobile applications. They regularly apply vetting processes to the deployed apps. Yet, some of these vetting processes might be inadequate or applied late. The late removal of applications might have unpleasant consequences for developers and users alike...
Main Authors: | Fadi Mohsen, Dimka Karastoyanova, George Azzopardi |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2022-12-01
|
Series: | Systems and Soft Computing |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2772941922000114 |
Similar Items
-
The death of privacy policies: How app stores shape GDPR compliance of apps
by: Julia Krämer
Published: (2024-04-01) -
Do the Right Thing: A Privacy Policy Adherence Analysis of over Two Million Apps in Apple iOS App Store
by: Hamad Alamri, et al.
Published: (2022-11-01) -
Measuring and Understanding Crowdturfing in the App Store
by: Qinyu Hu, et al.
Published: (2023-07-01) -
Sabahan community alert mobile apps /
by: Farhanah Atiqah Norki, 1992-, et al.
Published: (2015) -
User Preferences for Privacy Protection Methods in Mobile Health Apps: A Mixed-Methods Study
by: Leming Zhou, et al.
Published: (2020-12-01)