"I just hated it and I want my money back": Data-driven Understanding of Mobile VPN Service Switching Preferences in The Wild

Fuente: arXiv
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Auteurs principaux: Raj, Rohit, Newar, Mridul, Mondal, Mainack
Format: Preprint
Publié: 2024
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author Raj, Rohit
Newar, Mridul
Mondal, Mainack
author_facet Raj, Rohit
Newar, Mridul
Mondal, Mainack
contents Virtual Private Networks (VPNs) are a crucial Privacy-Enhancing Technology (PET) leveraged by millions of users and catered by multiple VPN providers worldwide; thus, understanding the user preferences for the choice of VPN apps should be of importance and interest to the security community. To that end, prior studies looked into the usage, awareness and adoption of VPN users and the perceptions of providers. However, no study so far has looked into the user preferences and underlying reasons for switching among VPN providers and identified features that presumably enhance users' VPN experience. This work aims to bridge this gap and shed light on the underlying factors that drive existing users when they switch from one VPN to another. In this work, we analyzed over 1.3 million reviews from 20 leading VPN apps, identifying 1,305 explicit mentions and intents to switch. Our NLP-based analysis unveiled distinct clusters of factors motivating users to switch. An examination of 376 blogs from six popular VPN recommendation sites revealed biases in the content, and we found ignorance towards user preferences. We conclude by identifying the key implications of our work for different stakeholders. The data and code for this work is available at https://github.com/Mainack/switch-vpn-datacode-sec24.
format Preprint
id arxiv_https___arxiv_org_abs_2403_01648
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle "I just hated it and I want my money back": Data-driven Understanding of Mobile VPN Service Switching Preferences in The Wild
Raj, Rohit
Newar, Mridul
Mondal, Mainack
Cryptography and Security
Human-Computer Interaction
Virtual Private Networks (VPNs) are a crucial Privacy-Enhancing Technology (PET) leveraged by millions of users and catered by multiple VPN providers worldwide; thus, understanding the user preferences for the choice of VPN apps should be of importance and interest to the security community. To that end, prior studies looked into the usage, awareness and adoption of VPN users and the perceptions of providers. However, no study so far has looked into the user preferences and underlying reasons for switching among VPN providers and identified features that presumably enhance users' VPN experience. This work aims to bridge this gap and shed light on the underlying factors that drive existing users when they switch from one VPN to another. In this work, we analyzed over 1.3 million reviews from 20 leading VPN apps, identifying 1,305 explicit mentions and intents to switch. Our NLP-based analysis unveiled distinct clusters of factors motivating users to switch. An examination of 376 blogs from six popular VPN recommendation sites revealed biases in the content, and we found ignorance towards user preferences. We conclude by identifying the key implications of our work for different stakeholders. The data and code for this work is available at https://github.com/Mainack/switch-vpn-datacode-sec24.
title "I just hated it and I want my money back": Data-driven Understanding of Mobile VPN Service Switching Preferences in The Wild
topic Cryptography and Security
Human-Computer Interaction
url https://arxiv.org/abs/2403.01648