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  • 标题:Measuring Odor Threshold Using a Simplified Olfactory Measurement Method
  • 本地全文:下载
  • 作者:Sayuri Daikoku ; Megumi Mitsuda ; Toshimi Tanamura
  • 期刊名称:人間-生活環境系学会英文誌
  • 印刷版ISSN:1345-1324
  • 电子版ISSN:1349-7723
  • 出版年度:2019
  • 卷号:21
  • 期号:1
  • 页码:1-8
  • DOI:10.1618/jhes.21.1
  • 出版社:Japanese Society of Human-Environment System
  • 摘要:IoT technology collects information from a lot of clients, which may relate to personal privacy. To protect the privacy, the clients would like to encrypt the raw data with their own keys before uploading. However, to make use of the information, the data mining technology with cloud computing is used for the knowledge discovery. Hence, it is an emergent issue of how to effectively performing data mining algorithm on the encrypted data. In this paper, we present a k-means clustering scheme with multi-user based on the IoT data. Although, there are many privacy-preserving k-means clustering protocols, they rarely focus on the situation of encrypting with different public keys. Besides, the existing works are inefficient and impractical. The scheme we propose in this paper not only solves the problem of evaluation on the encrypted data under different public keys but also improves the efficiency of the algorithm. It is semantic security under the semi-honest model according to our theoretical analysis. At last, we evaluate the experiment based on a real dataset, and comparing with previous works, the result shows that our scheme is more efficient and practical.
  • 关键词:Simplified Olfactory Measurement Method;odor concentration;odor threshold;degree of certainty;Triangle Odor Bag Method
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