Blowfish privacy: Tuning privacy-utility trade-offs using policies X He, A Machanavajjhala, B Ding Proceedings of the 2014 ACM SIGMOD international conference on Management of ¡¦, 2014 | 191 | 2014 |
DPT: differentially private trajectory synthesis using hierarchical reference systems X He, G Cormode, A Machanavajjhala, CM Procopiuc, D Srivastava Proceedings of the VLDB Endowment 8 (11), 1154-1165, 2015 | 169 | 2015 |
Composing differential privacy and secure computation: A case study on scaling private record linkage X He, A Machanavajjhala, C Flynn, D Srivastava Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications ¡¦, 2017 | 67 | 2017 |
Privatesql: a differentially private sql query engine I Kotsogiannis, Y Tao, X He, M Fanaeepour, A Machanavajjhala, M Hay, ... Proceedings of the VLDB Endowment 12 (11), 1371-1384, 2019 | 56 | 2019 |
Cryptϵ: Crypto-assisted differential privacy on untrusted servers A Roy Chowdhury, C Wang, X He, A Machanavajjhala, S Jha Proceedings of the 2020 ACM SIGMOD International Conference on Management of ¡¦, 2020 | 45 | 2020 |
Differential privacy in the wild: A tutorial on current practices & open challenges A Machanavajjhala, X He, M Hay Proceedings of the 2017 ACM International Conference on Management of Data ¡¦, 2017 | 42 | 2017 |
Shrinkwrap: efficient sql query processing in differentially private data federations J Bater, X He, W Ehrich, A Machanavajjhala, J Rogers Proceedings of the VLDB Endowment 12 (3), 2018 | 38 | 2018 |
Apex: Accuracy-aware differentially private data exploration C Ge, X He, IF Ilyas, A Machanavajjhala Proceedings of the 2019 International Conference on Management of Data, 177-194, 2019 | 35* | 2019 |
Investigating Statistical Privacy Frameworks from the Perspective of Hypothesis Testing. C Liu, X He, T Chanyaswad, S Wang, P Mittal Proc. Priv. Enhancing Technol. 2019 (3), 233-254, 2019 | 24 | 2019 |
Shrinkwrap: Differentially-private query processing in private data federations J Bater, X He, W Ehrich, A Machanavajjhala, J Rogers arXiv preprint arXiv:1810.01816, 2018 | 17 | 2018 |
Saqe: practical privacy-preserving approximate query processing for data federations J Bater, Y Park, X He, X Wang, J Rogers Proceedings of the VLDB Endowment 13 (12), 2691-2705, 2020 | 15 | 2020 |
A demonstration of VisDPT: Visual exploration of differentially private trajectories X He, N Raval, A Machanavajjhala Proceedings of the VLDB Endowment 9 (13), 1489-1492, 2016 | 11 | 2016 |
Computing local sensitivities of counting queries with joins Y Tao, X He, A Machanavajjhala, S Roy Proceedings of the 2020 ACM SIGMOD International Conference on Management of ¡¦, 2020 | 10 | 2020 |
Linear and range counting under metric-based local differential privacy Z Xiang, B Ding, X He, J Zhou 2020 IEEE International Symposium on Information Theory (ISIT), 908-913, 2020 | 9 | 2020 |
Analyzing your location data with provable privacy guarantees A Machanavajjhala, X He Handbook of Mobile Data Privacy, 97-127, 2018 | 9 | 2018 |
DP-cryptography: marrying differential privacy and cryptography in emerging applications S Wagh, X He, A Machanavajjhala, P Mittal Communications of the ACM 64 (2), 84-93, 2021 | 7 | 2021 |
Outis: crypto-assisted differential privacy on untrusted servers AR Chowdhury, C Wang, X He, A Machanavajjhala, S Jha | 7 | 2019 |
Dp-cryptography: Marrying differential privacy and cryptography in emerging applications S Wagh, X He, A Machanavajjhala, P Mittal arXiv preprint arXiv:2004.08887, 2020 | 6 | 2020 |
Kamino: Constraint-aware differentially private data synthesis C Ge, S Mohapatra, X He, IF Ilyas Proceedings of the VLDB Endowment 14 (10), 1886-1899, 2021 | 5 | 2021 |
Kamino: Constraint-aware differentially private data synthesis C Ge, S Mohapatra, X He, IF Ilyas arXiv preprint arXiv:2012.15713, 2020 | 5 | 2020 |