Practical Privacy-Preserving K-means Clustering

2020-6-16  2020-6-16  Clustering is a common technique for data analysis, which aims to partition data into sim-ilar groups. When the data comes from di erent sources, it is highly

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A Fine-grained Privacy-preserving k-means Clustering ...

2019-12-9  A Fine-grained Privacy-preserving k-means Clustering Algorithm Upon Negative Databases Abstract: Nowadays, privacy protection has become an important issue in

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(PDF) Privacy Preserving K-Means Clustering: A Secure ...

Privacy Preserving Machine Learning (PPML) helps to overcome this difficulty, employing cryptographic techniques, allowing knowledge discovery while ensuring data

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A Survey on A Privacy Preserving Technique using K

2021-2-27  In this paper two problems are considered in privacy preserving data mining.The first one is the protection of sensitive raw data, such as name, id num, address income

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(PDF) Efficient Privacy Preserving K-Means Clustering

This paper introduces an efficient privacy-preserving protocol for distributed K-means clustering over an arbitrary partitioned data, shared among N parties.

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Efficient and Privacy-Preserving k-Means Clustering for ...

... k-Means clustering, as the Unsupervised Learning scope, is a fundamental and critical data mining algorithm that has been widely used in practical applications.

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Privacy-preserving k-means clustering over vertically ...

On the design and quantification of privacy preserving data mining algorithms. In Proceedings of the Twentieth ACM SIGACT-SIGMOD-SIGART Symposium on Principles

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Research on K-Means Clustering Algorithm Over

2020-1-3  Aiming at the privacy-preserving problem in data mining process, this paper proposes an improved K-Means algorithm over encrypted data, called HK-means++ that uses the

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PRIVACY-PRESERVING DATA MINING: MODELS AND

2009-4-3  2009-4-3  PRIVACY-PRESERVING DATA MINING: MODELS AND ALGORITHMS Edited by CHARU C. AGGARWAL IBM T. J. Watson Research Center, Hawthorne, NY 10532 PHILIP S. YU

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An Overview of Privacy Preserving Data Mining -

2012-1-1  Privacy preserving in data mining is mainly applied to achieve privacy protection by different data characteristics in high-level data. Data release based privacy

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Efficient Privacy Preserving K-Means Clustering

2017-8-22  This paper introduces an efficient privacy-preserving protocol for dis-tributed K-means clustering over an arbitrary partitioned data, shared among N parties. Clustering is one of the fundamental algorithms used in the field of data mining. Advances in data acquisition methodologies have resulted in collection

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A Fine-grained Privacy-preserving k-means Clustering ...

2019-12-9  Nowadays, privacy protection has become an important issue in data mining. k-means algorithm is one of the most classical data mining algorithms, and it has been widely studied in the past decade. Negative database (NDB) is a new type of data representation which can protect privacy while supporting distance estimation, so it is promising to apply NDBs to privacy-preserving k-means

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Privacy Preserving Approximate K-means Clustering ...

2019-11-3  Specifically, the computational activity that we focus on is the K-means clustering, which is widely used for many data mining tasks. Our proposed variant of the K-means algorithm is capable of privacy preservation in the sense that it requires as input only binary encoded data, and is not allowed to access the true data vectors at any stage of ...

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Privacy Preserving K-Means Clustering

party’s data and learn the kmeans for the combined dataset keeping our threat model discussed in Section 3 in mind. 4.2 Original SMO07 algorithm The original algorithm proposed by Samet and Miri in [9] uses a multi-party addition algorithm to perform privacy-preserving k-means clustering on horizontally-partitioned data.

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1 INTRODUCTION IJSER

2016-9-9  lated work on privacy preserving data clustering. Existing k-means algorithm for data clustering has been discussed in sec-tion 3. Proposed method for SW-SDF based personalized pri-vacy for k-means clustering in section 4. Result analysis and conclusion in section 5 and section 6. ———————————————— •

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Distributed Privacy Preserving k-Means Clustering with ...

2008-11-7  secret sharing in a privacy preserving data mining algorithm is the work of Wright and Yang[14] to compute Bayesian net-works over vertically partitioned data. Similar to the work of Clifton and Vaidya[12], we address privacy preserving k-means clustering problem over vertically partitioned data,

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Practical Privacy-Preserving K-means Clustering

2020-6-16  Clustering is a common technique for data analysis, which aims to partition data into sim-ilar groups. When the data comes from di erent sources, it is highly desirable to maintain the privacy of each database. In this work, we study a popular clustering algorithm (K-means) and adapt it to the privacy-preserving context.

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Privacy Preserving Data Mining - Emory University

2018-4-16  Original K-means algorithm Laplace K-means algorithm • Laplace k-means can distinguish clusters that are far apart • Laplace k-means can’t distinguish small clusters that are close by.

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Privacy-Preserving and Outsourced Multi-user K-Means ...

2015-10-30  Abstract: Many techniques for privacy-preserving data mining (PPDM) have been investigated over the past decade. Such techniques, however, usually incur heavy computational and communication cost on the participating parties and thus entities with limited resources may have to refrain from participating in the PPDM process.

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Privacy-Preserving and Outsourced Multi-User k-Means ...

2021-8-1  arXiv:1412.4378v1 [cs.CR] 14 Dec 2014 Privacy-Preserving and Outsourced Multi-User k-Means Clustering Bharath K. Samanthula †, Fang-Yu Rao†, Elisa Bertino , Xun ...

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Efficient Privacy Preserving K-Means Clustering

2017-8-22  This paper introduces an efficient privacy-preserving protocol for dis-tributed K-means clustering over an arbitrary partitioned data, shared among N parties. Clustering is one of the fundamental algorithms used in the field of data mining. Advances in data acquisition methodologies have resulted in collection

Get Price

Distributed Privacy Preserving k-Means Clustering with ...

2008-11-7  secret sharing in a privacy preserving data mining algorithm is the work of Wright and Yang[14] to compute Bayesian net-works over vertically partitioned data. Similar to the work of Clifton and Vaidya[12], we address privacy preserving k-means clustering problem over vertically partitioned data,

Get Price

Privacy Preserving Data Mining - Emory University

2018-4-16  Original K-means algorithm Laplace K-means algorithm • Laplace k-means can distinguish clusters that are far apart • Laplace k-means can’t distinguish small clusters that are close by.

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A Fine-grained Privacy-preserving k-means Clustering ...

2019-12-9  Nowadays, privacy protection has become an important issue in data mining. k-means algorithm is one of the most classical data mining algorithms, and it has been widely studied in the past decade. Negative database (NDB) is a new type of data representation which can protect privacy while supporting distance estimation, so it is promising to apply NDBs to privacy-preserving k-means

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Poster: Privacy Preserving Distributed Data Mining for ...

2016-3-18  privacy preserving data mining algorithms from published theoretical research and analyzed three of them in detail. These are the K-Means algorithm on vertically partitioned data as well as neural network and ID3 decision tree algorithm on horizontally partitioned data. As we have seen, these privacy

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Privacy Preserving Data Mining Technique and Their ...

2017-10-12  concerns to ensure privacy of sensitive information. It enables multiple parties to conduct collaborative data mining while preserving the privacy of their data. In this work, a cloud computing based protocol for privacy-preserving distributed K-means clustering over horizontally partitioned data, shared between N parties, is proposed.

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A Literature Analysis on Privacy PreservingData Mining

2019-7-12  Surveying privacy preserving k -means clustering approaches apart from other privacy preserving data mining ones is important due to the use of this algorithm in important other areas, like image and signal processing where the problem of security is strongly posed [13]. Most of works in privacy preserving clustering are developed on the k ...

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Privacy-preserving data mining ACM SIGMOD Record

2000-5-16  Security and privacy implications of data mining. In ACId SIGMOD Workshop on Research Issues on Data Mining and Knowledge Discovery, pages 15-19, May 1996.]] Google Scholar; CO82 F.Y. Chin and G. O#soyoglu. Auditing and infrence control in statistical databases. IEBE Trans. Sof~w. Eng., SE-8(6):113-139, April 1982.]] Google Scholar Digital Library

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Privacy-preserving data mining in the malicious model

2009-5-11  In this section, we first discuss the previous work done in privacy-preserving data mining. Later, we describe the cryptographic tools and definitions used in this paper. 2.1 Related work Many different distributed privacy-preserving data mining algorithms

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Privacy-Preserving Data Mining - Models and Algorithms ...

From the reviews: "This book provides an exceptional summary of the state-of-the-art accomplishments in the area of privacy-preserving data mining, discussing the most important algorithms, models, and applications in each direction.

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