Data usage-based privacy and security issues in mobile app recommendation (MAR): a systematic literature review

Abstract

PurposeSimilarly, Zhu et al. (2014) and Zhang et al. (2014) stated that addressing privacy concerns with the recommendation process is necessary for the healthy development of app recommendation. Recently, Xiao et al. (2020) mentioned that a lack of effective privacy policy hinders the development of personalized recommendation services. According to the reported work, privacy protection technology methods are too limited for mobile focusing on data encryption, anonymity, disturbance, elimination of redundant data to protect the recommendation process from privacy breaches. So, this situation motivated us to conduct a systematic literature review (SLR) to provide the viewpoint of privacy and security concerns as mentioned in current state-of-the-art in the mobile app recommendation domain.Design/methodology/approachIn this work, the authors have followed Kitchenham guidelines (Kitchenham and Charters, 2007) to devise the SLR process. According to the guidelines, the SLR process has three main phases: (1) define, (2) conduct the search and (3) report the results. Furthermore, the authors used systematic mapping approach as well to ensure the whole process.FindingsBased on the selected studies, the authors proposed three main thematic taxonomies, including architectural style, security and privacy strategies, and user-usage in the mobile app recommendation domain. From the studies' synthesis viewpoint, it is observed that the majority of the research efforts have focused on the movie recommendation field, while the mainly used privacy scheme is homomorphic encryption. Finally, the authors suggested a set of future research dimensions useful for the potential researchers interested to perform the research in the mobile app recommendation domain.Originality/valueThis is an SLR article, based on existing published research, where the authors identified key issues and future directions.

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