TY - GEN
T1 - Privacy-Preserving ID3 Algorithms
T2 - 12th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2021
AU - Madathil, Nisha Thorakkattu
AU - Dankar, Fida K.
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Many real-life scenarios require the analysis of large amounts of data from multiple sources. Often, the data contain highly sensitive information and may be subject to privacy laws preventing its aggregation and sharing. Privacy-preserving data mining has emerged as a solution to this problem. It enables data scientists to analyze the distributed data without having to place it in a central location and while guaranteeing its privacy. Decision tree classification is a popular and widely studied machine learning technique for which many privacy-preserving versions exist. In this paper, we review recent privacy preserving implementations of the ID3 classification technique in a distributed environment and compare them in terms of efficiency and privacy. We consider cases where data is split horizontally over multiple parties.
AB - Many real-life scenarios require the analysis of large amounts of data from multiple sources. Often, the data contain highly sensitive information and may be subject to privacy laws preventing its aggregation and sharing. Privacy-preserving data mining has emerged as a solution to this problem. It enables data scientists to analyze the distributed data without having to place it in a central location and while guaranteeing its privacy. Decision tree classification is a popular and widely studied machine learning technique for which many privacy-preserving versions exist. In this paper, we review recent privacy preserving implementations of the ID3 classification technique in a distributed environment and compare them in terms of efficiency and privacy. We consider cases where data is split horizontally over multiple parties.
KW - ID3
KW - Privacy preserving data mining
KW - Secure Multiparty Computation
UR - http://www.scopus.com/inward/record.url?scp=85125188426&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85125188426&partnerID=8YFLogxK
U2 - 10.1109/UEMCON53757.2021.9666559
DO - 10.1109/UEMCON53757.2021.9666559
M3 - Conference contribution
AN - SCOPUS:85125188426
T3 - 2021 IEEE 12th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2021
SP - 16
EP - 22
BT - 2021 IEEE 12th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2021
A2 - Paul, Rajashree
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 1 December 2021 through 4 December 2021
ER -