Visible to the public SERS: A Security-Related and Evidence-Based Ranking Scheme for Mobile Apps

TitleSERS: A Security-Related and Evidence-Based Ranking Scheme for Mobile Apps
Publication TypeConference Paper
Year of Publication2019
AuthorsChowdhury, Nahida Sultana, Raje, Rajeev R.
Conference Name2019 First IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)
Keywordsapp distribution platforms, data mining, Databases, Google, Google PlayStore, Measurement, Mobile Apps, mobile computing, pubcrawl, ranking, Resiliency, Scalability, security, Security by Default, security of data, security-related and evidence-based ranking scheme, security-related comments, security-related internal aspect, sentiment analysis, SERS, smart mobile devices, smart phones, static taint analysis, subjective logic, Trust, User Ratings
AbstractIn recent years, the number of smart mobile devices has rapidly increased worldwide. This explosion of continuously connected mobile devices has resulted in an exponential growth in the number of publically available mobile Apps. To facilitate the selection of mobile Apps, from various available choices, the App distribution platforms typically rank/recommend Apps based on average star ratings, the number of downloads, and associated reviews - the external aspect of an App. However, these ranking schemes typically tend to ignore critical internal aspects (e.g., security vulnerabilities) of the Apps. Such an omission of internal aspects is certainly not desirable, especially when many of the users do not possess the necessary skills to evaluate the internal aspects and choose an App based on the default ranking scheme which uses the external aspect. In this paper, we build upon our earlier efforts by focusing specifically on the security-related internal aspect of an App and its combination with the external aspect computed from the user reviews by identifying security-related comments.We use this combination to rank-order similar Apps. We evaluate our approach on publicly available Apps from the Google PlayStore and compare our ranking with prevalent ranking techniques such as the average star ratings. The experimental results indicate the effectiveness of our proposed approach.
Citation Keychowdhury_sers_2019