TY - GEN
T1 - Privacy preserving ID3 algorithm over horizontally partitioned data
AU - Xiao, Mingjun
AU - Huang, Liusheng
AU - Shen, Hong
AU - Luo, Yonglong
PY - 2005
Y1 - 2005
N2 - For the problem of decision tree classification with privacy concerns, we propose several efficient secure multi-party computation protocols to construct a privacy preserving ID3 algorithm over horizontally partitioned data among multiple parties. Our algorithm presents the first solution to privacy preserving decision tree classification among more than two parties. We also make a performance comparison with the existing solution, which is only applicable to the two-party case. The result shows that our solution has a significantly better performance.
AB - For the problem of decision tree classification with privacy concerns, we propose several efficient secure multi-party computation protocols to construct a privacy preserving ID3 algorithm over horizontally partitioned data among multiple parties. Our algorithm presents the first solution to privacy preserving decision tree classification among more than two parties. We also make a performance comparison with the existing solution, which is only applicable to the two-party case. The result shows that our solution has a significantly better performance.
UR - https://www.scopus.com/pages/publications/33745171439
M3 - Conference contribution
AN - SCOPUS:33745171439
SN - 0769524052
SN - 9780769524054
T3 - Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings
SP - 239
EP - 243
BT - Proceedings - Sixth International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2005
T2 - 6th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2005
Y2 - 5 December 2005 through 8 December 2005
ER -