- 期刊
Privacy Preserving K-nearest Neighbor Classification
並列摘要
This paper considers how to conduct k-nearest neighbor classification in the following scenario: multiple parties, each having a private data set, want to collaboratively build a k-nearest neighbor classifier without disclosing their private data to each other or any other parties. Specifically, the data are vertically partitioned in that all parties have data about all the instances involved, but each party has its own view of the instances - each party works with its own attribute set. Because of privacy constraints, developing a secure framework to achieve such a computation is both challenging and desirable. In this paper, we develop a secure protocol for multiple parties to conduct the desired computation. All the parties participate in the encryption and in the computation involved in learning the k-nearest neighbor classifiers.
延伸閱讀
- Lin, W. S., & Lee, C. P. (2012). A Novel Distance-Based k-Nearest Neighbor Voting Classifier. 電腦學刊, 23(3), 26-34. https://www.airitilibrary.com/Article/Detail?DocID=19911599-201209-201211050061-201211050061-26-34
- 古祐嘉（2009）。Adaptive K-Nearest Neighbor Algorithm〔碩士論文，元智大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0009-1106200913100600
- 林思宇（2018）。Prior-free Nearest Neighbors based Rare Category Detection〔碩士論文，國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU201800483
- 彭得裕（2021）。Study on Signal Identification by Applying the K-Nearest Neighbors Algorithm〔碩士論文，健行科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0022-0604202113383700
- Gu, Y., Yu, G., & Yu, X. N. (2014). An Efficient Method for k Nearest Neighbor Searching in Obstructed Spatial Databases. Journal of Information Science and Engineering, 30(5), 1569-1583. https://doi.org/10.6688/JISE.2014.30.5.15