SE-P²μm: Secure and Efficient Privacy-Preserving User-Profile Matching Protocol for Social Networks.
Jianhong ZhangHaoting HaoHongwei SuPublished in: IEEE Trans. Comput. Soc. Syst. (2023)
Keyphrases
- privacy preserving
- vertically partitioned data
- user profiles
- scalar product
- secure multiparty computation
- homomorphic encryption
- multi party
- horizontally partitioned data
- social networks
- privacy preserving data mining
- secure multi party computation
- user privacy
- user preferences
- data privacy
- privacy preservation
- sensitive data
- lightweight
- sensitive information
- privacy preserving association rule mining
- record linkage
- semi honest
- user interests
- encryption scheme
- privacy issues
- data sharing
- providing personalized
- privacy sensitive
- cryptographic protocols
- data perturbation
- social media
- dot product
- differential privacy
- privacy concerns
- online social networks
- peer to peer
- information retrieval systems
- collaborative filtering