隐私集合求交(Private Set Intersection,PSI)是一种保护数据隐私的集合计算技术,允许互不信任的各方协同计算私有数据的交集,且不透露交集以外的任何信息。PSI技术被广泛研究和应用,主要从提升性能和探索新型应用场景两个方面发力。首...隐私集合求交(Private Set Intersection,PSI)是一种保护数据隐私的集合计算技术,允许互不信任的各方协同计算私有数据的交集,且不透露交集以外的任何信息。PSI技术被广泛研究和应用,主要从提升性能和探索新型应用场景两个方面发力。首先详细梳理两方PSI的研究进展,分析和评估业界先进的算法协议;其次以卫星互联网新型应用场景为例,探索提出高性能两方PSI应用方案,实验测试不同数据类型在多种网络环境下的性能,给出新型场景下的PSI实践范式。最后进行总结与展望,给出了PSI的发展思考与建议。展开更多
As an extension of overlap functions, pseudo-semi-overlap functions are a crucial class of aggregation functions. Therefore, (I, PSO)-fuzzy rough sets are introduced, utilizing pseudo-semi-overlap functions, and furth...As an extension of overlap functions, pseudo-semi-overlap functions are a crucial class of aggregation functions. Therefore, (I, PSO)-fuzzy rough sets are introduced, utilizing pseudo-semi-overlap functions, and further extended for applications in image edge extraction. Firstly, a new clustering function, the pseudo-semi-overlap function, is introduced by eliminating the symmetry and right continuity present in the overlap function. The relaxed nature of this function enhances its applicability in image edge extraction. Secondly, the definitions of (I, PSO)-fuzzy rough sets are provided, using (I, PSO)-fuzzy rough sets, a pair of new fuzzy mathematical morphological operators (IPSOFMM operators) is proposed. Finally, by combining the fuzzy C-means algorithm and IPSOFMM operators, a novel image edge extraction algorithm (FCM-IPSO algorithm) is proposed and implemented. Compared to existing algorithms, the FCM-IPSO algorithm exhibits more image edges and a 73.81% decrease in the noise introduction rate. The outstanding performance of (I, PSO)-fuzzy rough sets in image edge extraction demonstrates their practical application value.展开更多
文摘隐私集合求交(Private Set Intersection,PSI)是一种保护数据隐私的集合计算技术,允许互不信任的各方协同计算私有数据的交集,且不透露交集以外的任何信息。PSI技术被广泛研究和应用,主要从提升性能和探索新型应用场景两个方面发力。首先详细梳理两方PSI的研究进展,分析和评估业界先进的算法协议;其次以卫星互联网新型应用场景为例,探索提出高性能两方PSI应用方案,实验测试不同数据类型在多种网络环境下的性能,给出新型场景下的PSI实践范式。最后进行总结与展望,给出了PSI的发展思考与建议。
文摘As an extension of overlap functions, pseudo-semi-overlap functions are a crucial class of aggregation functions. Therefore, (I, PSO)-fuzzy rough sets are introduced, utilizing pseudo-semi-overlap functions, and further extended for applications in image edge extraction. Firstly, a new clustering function, the pseudo-semi-overlap function, is introduced by eliminating the symmetry and right continuity present in the overlap function. The relaxed nature of this function enhances its applicability in image edge extraction. Secondly, the definitions of (I, PSO)-fuzzy rough sets are provided, using (I, PSO)-fuzzy rough sets, a pair of new fuzzy mathematical morphological operators (IPSOFMM operators) is proposed. Finally, by combining the fuzzy C-means algorithm and IPSOFMM operators, a novel image edge extraction algorithm (FCM-IPSO algorithm) is proposed and implemented. Compared to existing algorithms, the FCM-IPSO algorithm exhibits more image edges and a 73.81% decrease in the noise introduction rate. The outstanding performance of (I, PSO)-fuzzy rough sets in image edge extraction demonstrates their practical application value.