A Survey on Privacy Issues in Mobile Social Networks

• Main Authors: Akshita Maradapu Vera Venkata Sai, Yingshu Li
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Differential privacy; location privacy; mobile social networks; privacy; user privacy
• Online Access: https://ieeexplore.ieee.org/document/9142169/

Mobile Social Networks (MSNs) are a category of social networks that have features of both traditional OSNs and Location-Based Social Networks (LBSNs). MSNs provide users with an opportunity to explore social media, connect with people nearby, or with those sharing similar interests. The ease with which people can connect and use these networks to obtain information, share user-centric data, and request services on the go through their mobile devices as long as they have access to the internet has made MSNs omnipresent. Due to the widespread nature of MSNs and the lack of effective privacy-preserving architecture makes them a target for several attacks by adversaries and the users of the networks are completely vulnerable to these privacy breaches. With the advancements in technology, the number of attacks and their possible solutions is complex and expansive. Therefore, there is a need to properly categorize them to understand the intricacies of different attacks and the concepts used by researchers to devise different solutions. This survey on privacy issues in MSNs serves as a way to provide an introduction to MSNs. We categorize privacy in MSN on the basis of the aspect they effect and summarize the different threats in each category. Furthermore, we provide an elaborate classification of the various privacy-preserving solutions proposed in recent research works, under each category of privacy. We also review different datasets and data generation tools that can be used by future researchers in this field.