An Efficient Designated Dating Matching Scheme for Online Social Network

The significance of privacy and security in online social networks is to protect sensitive information, prevent unauthorized access, and build trust among users while ensuring a secure online environment. This paper proposes a friendship matching system based on the Parlier encryption algorithm, aiming at addressing existing privacy breaches and data misuse issues on current friendship platforms, significantly improving matching accuracy. First, filter the data items that users care about more in the database so as to make the appropriate friends. Then, according to the homomorphic encryption of paillier algorithm, in the case of ciphertext, the weight of each data item is calculated to the selected users. Finally, the Euclidean distance is used to calculate the similarity between users and select the appropriate dating users. Experimental results demonstrate that the proposed system exhibits strong performance and feasibility in preserving user privacy and data security.