Combined fuzzy clustering and firefly algorithm for privacy preserving in social networks
作者：
Highlights：
• A combined fuzzy clustering and firefly algorithm (KFCFA) is presented.
• A constrained multi-objective function is introduced for privacy preserving in social networks.
• The proposed anonymity methodology can be performed at data level and graph level.
• Our methodology guarantees to fulfill K-anonymity, L-diversity and T-closeness conditions.
• The method is simulated over four social networks: Facebook, Google+, Twitter and Youtube.
摘要
•A combined fuzzy clustering and firefly algorithm (KFCFA) is presented.•A constrained multi-objective function is introduced for privacy preserving in social networks.•The proposed anonymity methodology can be performed at data level and graph level.•Our methodology guarantees to fulfill K-anonymity, L-diversity and T-closeness conditions.•The method is simulated over four social networks: Facebook, Google+, Twitter and Youtube.
论文关键词：Firefly algorithm,Fuzzy clustering,K-anonymity,Privacy preserving,Social networks
论文评审过程：Received 26 March 2019, Revised 13 September 2019, Accepted 19 September 2019, Available online 19 September 2019, Version of Record 26 September 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.112968
