Abstract
The last decade or so has witnessed a sharp rise in the growth of mobile devices. These mobile devices and wireless communication technologies enable people around the globe to instantaneously communicate with each other. This leads to the emergence of a new type of social networking known as Mobile Social Network (MSN). MSN offers a wide range of useful applications, such as group text services, social gaming, location-based services (to name a few). One of the popular applications of MSN is matchmaking where people match their interests/hobbies to find the like-minded people for a possible friendship. However, revealing personal hobbies can pose significant threats on a user’s privacy. Therefore, a privacy preserving evaluation method is needed to find the similarity between users’ interests. There are various techniques to achieve privacy preserving matchmaking, such as commutative encryption, oblivious transfer and homomorphic encryption. This paper discusses the feasibility of commutative encryption by evaluating recently proposed schemes. The paper attempts to identify various shortcomings in the present work and discusses future directions.
Highlights
A Mobile Social Network (MSN) enables its users to make social ties between them using mobile devices and communication technologies [1]
MSN offers many useful applications such as locations-based services where nearby people share their experiences about restaurants, shopping malls, and social gaming that allows friends to play online games with each other
One of the most popular applications of MSN is matchmaking where people find the similarity between their profiles to establish a possible friendship
Summary
A Mobile Social Network (MSN) enables its users to make social ties between them using mobile devices and communication technologies [1]. One of the most popular applications of MSN is matchmaking where people find the similarity between their profiles to establish a possible friendship. Peoples’ profiles consist of personal information such as political affiliations, sexual orientation and health status etc. Disclosure of such information to a stalker may seriously jeopardize the privacy of a user. Many researchers have proposed privacy preserving matchmaking schemes to privately evaluate the interest-wise similarity between their profiles. We can classify these techniques as a private set intersection (PSI) or private cardinality set intersection (PCSI) problem [2], [9], [10].
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