Security‐centric ranking algorithm and two privacy scores to mitigate intrusive apps

Smartphone users are constantly facing the risks of losing their private information to third-party mobile applications. Studies have revealed that vast majority either do not pay attention privacy or unable comprehend messages. Developers though exploited this fact by asking grant apps an enormous number permissions. In article, we propose and evaluate a new security-centric ranking algorithm built on top Elasticsearch engine help evade such apps. The calculates intrusiveness score for app based its requested permissions, received system actions, users' preferences. As such, further approach capture these We using million Android applications, contextual data APK files, collect from Google Play store. results show scoring reranking steps add minor overhead. Moreover, participants user studies gave positive feedback preferences solicitation approach. These suggest our proposed would definitely protect pushes developers into requesting least amount privileges. Still, there many endanger privacy.