The basic idea of blind vector transformation protocol is allowing two untrusted parties to transform two vectors into the blind ones by following a series of private and identical steps, e.g., adding a random vector, shuffling in the same order. Since the transformation follows the same step, the matching results (e.g. the number of matched interest and profiles) keep unchanged before and after the transformation, which enable the untrusted participants compare the profile without leaking their real interest or profile information. The major challenge of the blind vector is how to hide the real value of the interest or profile of the participants. The basic idea is that two untrusted participants will contribute a part of this transformation while each of them cannot recover the real interest or profile. a privacy-preserving personal profile matching in mobile social networks. By using secure multi-party computation (SMC) techniques, it can achieves that, an initiating user can find from a group of users the one whose profile best matches with his/her. It is proposed the concept of Fine-Grained Private Matching, which allows finer differentiation between PMSN users and can support a wide range of matching metrics at different privacy levels. Different from these existing works, we separate users’ profiles from their interest the unfairness issue. The proposed scheme could well thwart this novel attack and thus achieve a better security. for the first time. They propose a novel Run-away attack, which may potentially introduce