Privacy-Preserving Decision Trees over Vertically Partitioned Data
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The vertical FL setting requires a more complex mechanism to decompose the loss function at each party than horizontal FL.
“Unlike sample-partitioned/horizontal FL, the vertical FL setting requires a more complex mechanism to decompose the loss function at each party [5], [15], [16].”
From SecureBoost: A Lossless Federated Learning Framework (2021) · cites this paper as [16]
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Kikuchi, H., Ito, K., Ushida, M., Tsuda, H., & Yamaoka, Y. (2013) · International Conference on Advanced Information Networking and Applications (AINA) · doi:10.1109/aina.2013.140 · Cited by 4 · see citing works
Cloud-Assisted Privacy-Preserving Classification for IoT Applications
Yang, L., & Li, F. (2018) · IEEE Conference on Communications and Network Security · doi:10.1109/cns.2018.8433157 · Cited by 4 · see citing works
Privacy-preserving ranking over vertically partitioned data
Kianmehr, K., & Koochakzadeh, N. (2012) · EDBT/ICDT Workshops · doi:10.1145/2320765.2320825 · Cited by 4 · see citing works
Gangrade, A. (2012) · IOSR Journal of Computer Engineering · doi:10.9790/0661-0760412 · Cited by 3 · see citing works
HERB+: Evolving an Industrial-Strength Privacy-Preserving Machine Learning Framework
Liao, Q., Santos, A. C., Cabral, B., Fernandes, J. P., & Lourenço, N. (2022) · IEEE Pacific Rim International Symposium on Dependable Computing (PRDC) · doi:10.1109/prdc55274.2022.00035 · Cited by 3 · see citing works
Borisov, A. V., Bosov, A. V., & Ivanov, A. V. (2023) · Programming and Computer Software · doi:10.1134/s0361768823040047 · Cited by 3 · see citing works
SpecFL: An Efficient Speculative Federated Learning System for Tree-based Model Training
Zhang, Y., Zhao, L., Che, C., Wang, X., Meng, D., & Hou, R. (2024) · IEEE International Symposium on High-Performance Computer Architecture (HPCA) · doi:10.1109/hpca57654.2024.00068 · Cited by 3 · see citing works
Local Distortion Hiding in Financial Technology application: a case study with a benchmark data set
Feretzakis, G., Kalles, D., & Verykios, V. S. (2019) · International Conference on Information, Intelligence, Systems & Applications (IISA) · doi:10.1109/iisa.2019.8900733 · Cited by 3 · see citing works
Advanced Privacy-Preserving Data Management and Analysis
Trombetta, A., Jiang, W., & Bertino, E. (2010) · Advanced information and knowledge processing · doi:10.1007/978-1-84996-238-4_2 · Cited by 3 · see citing works
Speeding Up Secure Computations via Embedded Caching
Zhai, K., Ng, W. K., Herianto, A. R., & Han, S. (2009) · SIAM International Conference on Data Mining · doi:10.1137/1.9781611972795.40 · Cited by 3 · see citing works
An Efficient Cacheable Secure Scalar Product Protocol for Privacy-Preserving Data Mining
Tran, D. H., Ng, W. K., Lim, H. W., & Nguyen, H.-L. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-23544-3_27 · Cited by 3 · see citing works
- Authors
- Vaidya, J., & Clifton, C.
- Affiliations
- Rutgers, The State University of New Jersey (US)
- Purdue University West Lafayette (US)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2005
- Pages
- 139-152
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2679684481
- Cited by
- 144
- References
- 21
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 4 · 2023: 3 · 2022: 8 · 2021: 6 · 2020: 7 · 2019: 10 · 2018: 5 · 2017: 10 · 2016: 8 · 2015: 7 · 2014: 8 · 2013: 10 · 2012: 10
- FWCI
- 5.23
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptography and Data Security
- Physical Sciences › Computer Science › Information Systems › Cloud Data Security Solutions
- Keywords
- privacy-preserving data mining, decision tree, ID3, vertically partitioned data, distributed knowledge discovery, classification, information-theoretic security, multi-party data sharing
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