Abstract
Due to the fast development of Internet and the related IT technologies, it becomes more and more easier to access a large amount of data. k-means clustering is a powerful and frequently used technique in data mining. Many research papers about privacy-preserving k-means clustering were published. In this paper, we analyze the existing privacy-preserving k-means clustering schemes based on the cryptographic techniques. We show those schemes will cause the privacy breach and cannot output the correct results due to the faults in the protocol construction. Furthermore, we analyze our proposal as an option to improve such problems but with intermediate information breach during the computation.
| Original language | English |
|---|---|
| Pages (from-to) | 1246-1250 |
| Number of pages | 5 |
| Journal | IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences |
| Volume | E92-A |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Jan 1 2009 |
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All Science Journal Classification (ASJC) codes
- Signal Processing
- Computer Graphics and Computer-Aided Design
- Electrical and Electronic Engineering
- Applied Mathematics
Cite this
Security and correctness analysis on privacy-preserving k-means clustering schemes. / Su, Chunhua; Bao, Feng; Zhou, Jianying; Takagi, Tsuyoshi; Sakurai, Kouichi.
In: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol. E92-A, No. 4, 01.01.2009, p. 1246-1250.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Security and correctness analysis on privacy-preserving k-means clustering schemes
AU - Su, Chunhua
AU - Bao, Feng
AU - Zhou, Jianying
AU - Takagi, Tsuyoshi
AU - Sakurai, Kouichi
PY - 2009/1/1
Y1 - 2009/1/1
N2 - Due to the fast development of Internet and the related IT technologies, it becomes more and more easier to access a large amount of data. k-means clustering is a powerful and frequently used technique in data mining. Many research papers about privacy-preserving k-means clustering were published. In this paper, we analyze the existing privacy-preserving k-means clustering schemes based on the cryptographic techniques. We show those schemes will cause the privacy breach and cannot output the correct results due to the faults in the protocol construction. Furthermore, we analyze our proposal as an option to improve such problems but with intermediate information breach during the computation.
AB - Due to the fast development of Internet and the related IT technologies, it becomes more and more easier to access a large amount of data. k-means clustering is a powerful and frequently used technique in data mining. Many research papers about privacy-preserving k-means clustering were published. In this paper, we analyze the existing privacy-preserving k-means clustering schemes based on the cryptographic techniques. We show those schemes will cause the privacy breach and cannot output the correct results due to the faults in the protocol construction. Furthermore, we analyze our proposal as an option to improve such problems but with intermediate information breach during the computation.
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UR - http://www.scopus.com/inward/citedby.url?scp=77956034921&partnerID=8YFLogxK
U2 - 10.1587/transfun.E92.A.1246
DO - 10.1587/transfun.E92.A.1246
M3 - Article
AN - SCOPUS:77956034921
VL - E92-A
SP - 1246
EP - 1250
JO - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
JF - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
SN - 0916-8508
IS - 4
ER -