PP-STAT: An Efficient Privacy-Preserving Statistical Analysis Framework using Homomorphic Encryption.

@inproceedings{choi-2025-ppstat, author = {Hyunmin Choi}, editor = {Meeyoung Cha and Carl Yang and Chanyoung Park and Senjuti Basu Roy and Noseong Park and Zhenhui Jessie Li and Carl Yang and Senjuti Basu Roy and Zhenhui Jessie Li and Jaap Kamps and Kijung Shin and Bryan Hooi and Lifang He}, title = {{PP-STAT: An Efficient Privacy-Preserving Statistical Analysis Framework using Homomorphic Encryption}}, booktitle = {{Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025}}, pages = {448--457}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3746252.3761194}, doi = {https://doi.org/10.1145/3746252.3761194} }