Fuzzy-based multiparty privacy management in social media using modified elliptic curve cryptography

Sharing data via social media may affect the privacy of other user’s in social media. Also, multiparty privacy management is absent in social media, which leads the users incapable of managing to whom the data are shared. Because of the privacy conflicts, it is not easy to combine the privacy preferences of multiple users. For resolving the privacy conflicts in social media, more methods are required. This study promotes a fuzzy-based multiparty privacy management in social media using modified elliptic curve cryptography. The evaluation model used a method based on secure multiparty computing. Next, the fuzzy technique for order of preference by similarity to ideal solution (fuzzy TOPSIS) method is used to rank and select the participants. Finally, data encryption is performed using a modified elliptic curve encryption (MECC). Here, the optimal selection of private key is performed using the cuckoo search optimization algorithm (CSOA). With these presented techniques, the users can manage who the data are shared. In order to overcome privacy conflicts, users may first rank and select the participants based on fuzzy TOPSIS. Also, the privacy of the users is not affected by using the MECC-based data encryption framework. The presented work is implemented on the JAVA platform. The outcomes of the experiment prove that the presented approach outperforms the other existing approaches.