TY - GEN
T1 - An efficient private evaluation of a decision graph
AU - Sudo, Hiroki
AU - Nuida, Koji
AU - Shimizu, Kana
N1 - Funding Information:
Acknowledgements. A part of this work is supported by Okawa Foundation Research Grant and JST CREST grant numbers: JPMJCR1503, JPMJCR1688, JPMJCR14D6.
Funding Information:
A part of this work is supported by Okawa Foundation Research Grant and JST CREST grant numbers: JPMJCR1503, JPMJCR1688, JPMJCR14D6.
PY - 2019
Y1 - 2019
N2 - A decision graph is a well-studied classifier and has been used to solve many real-world problems. We assumed a typical scenario between two parties in this study, in which one holds a decision graph and the other wants to know the class label of his/her query without disclosing the graph and query to the other. We propose a novel protocol for this scenario that can obliviously evaluate a graph that is designed by an efficient data structure called the graph level order unary degree sequence (GLOUDS). The time and communication complexities of this protocol are linear to the number of nodes in the graph and do not include any exponential factors. The experiment results revealed that the actual runtime and communication size were well concordant with theoretical complexities. Our method can process a graph with approximately 500 nodes in only 11 s on a standard laptop computer. We also compared the runtime of our method with that of previous methods and confirmed that it was one order of magnitude faster than the previous methods.
AB - A decision graph is a well-studied classifier and has been used to solve many real-world problems. We assumed a typical scenario between two parties in this study, in which one holds a decision graph and the other wants to know the class label of his/her query without disclosing the graph and query to the other. We propose a novel protocol for this scenario that can obliviously evaluate a graph that is designed by an efficient data structure called the graph level order unary degree sequence (GLOUDS). The time and communication complexities of this protocol are linear to the number of nodes in the graph and do not include any exponential factors. The experiment results revealed that the actual runtime and communication size were well concordant with theoretical complexities. Our method can process a graph with approximately 500 nodes in only 11 s on a standard laptop computer. We also compared the runtime of our method with that of previous methods and confirmed that it was one order of magnitude faster than the previous methods.
KW - Decision graph
KW - GLOUDS
KW - Homomorphic encryption
UR - http://www.scopus.com/inward/record.url?scp=85061098792&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85061098792&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-12146-4_10
DO - 10.1007/978-3-030-12146-4_10
M3 - Conference contribution
AN - SCOPUS:85061098792
SN - 9783030121457
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 143
EP - 160
BT - Information Security and Cryptology – ICISC 2018 - 21st International Conference, Revised Selected Papers
A2 - Lee, Kwangsu
PB - Springer Verlag
T2 - 21st International Conference on Information Security and Cryptology, ICISC 2018
Y2 - 28 November 2018 through 30 November 2018
ER -