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Privacy Preserving Clustering
[chapter]
2005
Lecture Notes in Computer Science
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The crucial step in our privacy-preserving k-means is privacy-preserving computation of cluster means. ...
In this paper, we present the design and analysis of a privacy-preserving k-means clustering algorithm, where only the cluster means at the various steps of the algorithm are revealed to the participating ...
Privacy-preserving k-means In order, to create a privacy-preserving version of k-means that does not use a TTP we have to devise a privacy-preserving protocol to compute the cluster means. ...
doi:10.1007/11555827_23
fatcat:vgo23ozkbzeydlaqk7i5zy4fu4
Importance of Data Standardization in Privacy-Preserving K-Means Clustering
[chapter]
2009
Lecture Notes in Computer Science
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Privacy-preserving k-means clustering assumes that there are at least two parties in the secure interactive computation. ...
Also, we provide a solution for the secure data standardization in the privacypreserving k-means clustering. ...
In this paper, we study data variable standardization problems in the privacy preserving k-means clustering problem using the secure approximation algorithms. ...
doi:10.1007/978-3-642-04205-8_23
fatcat:7xjhsamhavhgnjy7oxotibgjpa
Differentially Private Clustering in High-Dimensional Euclidean Spaces
2017
International Conference on Machine Learning
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In this work, we give differentially private and efficient algorithms achieving strong guarantees for k-means and k-median clustering when d = Ω(polylog(n)). ...
We study the problem of clustering sensitive data while preserving the privacy of individuals represented in the dataset, which has broad applications in practical machine learning and data analysis tasks ...
of all k centers while still preserving differential privacy. ...
dblp:conf/icml/BalcanDLMZ17
fatcat:57fau6vqcfg6rnjam6cvrfogg4
Differential identifiability clustering algorithms for big data analysis
2021
Science China Information Sciences
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Individual privacy preservation has become an important issue with the development of big data technology. ...
The experimental results show that both DI k-means and DI k-prototypes algorithms satisfy differential identifiability. ...
By means of Algorithm 1, the database D can release the approximate value of cluster centers to achieve privacy preservation. ...
doi:10.1007/s11432-020-2910-1
fatcat:4odlynwnejapjoxgebuhwmrrea
A Random Matrix Approach to Differential Privacy and Structure Preserved Social Network Graph Publishing
[article]
2013
arXiv
pre-print
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We show that as compared to existing approaches for differential private approximation of eigenvectors, our approach is computationally efficient, preserves the utility and satisfies differential privacy ...
Among the various privacy preserving models, Differential privacy provides the strongest privacy guarantees. ...
Since spectral clustering employs k−means, each set Ci can have different cluster distributions. ...
arXiv:1307.0475v1
fatcat:q5zb2qh2prcznkb4ldwuss2oy4
Privacy-Preserving Distributed Clustering for Electrical Load Profiling
[article]
2020
arXiv
pre-print
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Using the proposed framework, we modify several commonly used clustering methods, including k-means, fuzzy C-means, and Gaussian mixture model, to provide privacy-preserving distributed clustering methods ...
The privacy and complexity of the proposed privacy-preserving distributed clustering framework are analyzed. ...
PRIVACY-PRESERVING DISTRIBUTED CLUSTERING FRAMEWORK This section describes the privacy-preserving distributed clustering framework for k-means, FCA, and GMM incorporating the proposed PP-AAC algorithm. ...
arXiv:2002.12769v1
fatcat:34yr53nrfvdylgfgn2ao5clpgy
New privacy preserving clustering methods for secure multiparty computation
2016
Artificial intelligence research
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In this paper, we propose clustering methods such as k-means and NG for SMC and show the effectiveness in numerical simulation. ...
Many researches on privacy preserving data mining have been done. ...
PRIVACY PRESERVING k-MEANS AND NG
Proposed k-means method for SMC A system consisting of a client and m parties is assumed (see Figure 1 ). ...
doi:10.5430/air.v6n1p27
fatcat:rbtapxtwlnbzpbdt4aeju3mcgq
Privacy Preservation in Online Social Networks Using Multiple-Graph-Properties-Based Clustering to Ensure k-Anonymity, l-Diversity, and t-Closeness
2021
Electronics
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Various privacy preservation methods have been introduced recently at the user and network levels, but ensuring k-anonymity and higher privacy model requirements such as l-diversity and t-closeness in ...
Furthermore, the clusters ensure improved k-anonymization by a novel one-pass anonymization algorithm to address l-diversity and t-closeness privacy requirements. ...
The LECC method achieved privacy preservation in the shortest time of all three techniques, as it relies on simple K-means clustering for ECC and LECC. ...
doi:10.3390/electronics10222877
fatcat:rd3hljolwjh5jmv67duntcnq5a
Privacy Preserving in Data Mining by Normalization
2014
International Journal of Computer Applications
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Our purpose is to use it for preserving privacy through data mining. We use K-means clustering to validate the proposed approach and validate for accuracy. ...
and K-mean clustering techniques in our proposed system. ...
doi:10.5120/16797-6509
fatcat:gixmtn34djf63bn7rsqm653674
A Proposed Technique for Privacy Preservation by Anonymization Method Accomplishing Concept of K-Means Clustering and DES
2017
International Journal for Research in Applied Science and Engineering Technology
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We discuss PPDM by Anonymization Method in which we use K-means clustering in order to divide the given data and DES algorithm for encryption of data in order to prevent sensitive data from attacker. ...
Privacy-Preserving Data Mining also an essential branch of the data mining and an exciting topic in privacy preservation has gain particular attention in current years. ...
To preserve privacy, model of k-anonymity has been proposed by the Sweeney [2] which achieve k anonymity by means of generalization and the Suppression , K-anonymity, it is difficult for an imposter ...
doi:10.22214/ijraset.2017.8226
fatcat:zo5nq6zt5veazimmcic7bh7j7q
Privacy Preserving Clustering on Distorted data
2012
IOSR Journal of Computer Engineering
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The data mining utility k-means clustering is used on these distorted datasets. Our experimental results use a real world dataset. ...
In designing various security and privacy related data mining applications, privacy preserving has become a major concern. ...
Thus, a complete privacy can be obtained in k-means cluster analysis and is also proved in privacy metrics.
V. ...
doi:10.9790/0661-0522529
fatcat:ya6li4lftbbttlmf6flhnhon7u
SVDC: Preserving Privacy in Clustering using Singular Value Decomposition
2008
Journal of Information Privacy and Security
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Our proposed method Clustering Singular Value Decomposition (CLUST-SVD) distorts only confidential numerical attributes to meet privacy requirements, while preserving general features for k-means clustering ...
We focus primarily on privacy preserving data clustering. ...
We have presented a Singular Value Decomposition method for data distortion to achieve privacy-preserving in data mining applications. We focus primarily on privacy preserving k-means clustering. ...
doi:10.1080/2333696x.2008.10855839
fatcat:rho6k53mufeplmfu4uouucksai
Grouping of Distributed Data at Multiple Sites by Sustaining the Privacy of Data
2020
Procedia Computer Science
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The proposed work discusses a privacy preserving clustering method to group identical data. One of the major challenges while modeling is to compute a representative for each cluster. ...
The proposed work discusses a privacy preserving clustering method to group identical data. One of the major challenges while modeling is to compute a representative for each cluster. ...
It is observed the SSE for the proposed privacy preserving k-means clustering approach is lesser than the base clustering method used for privacy preserving clustering. ...
doi:10.1016/j.procs.2020.04.181
fatcat:pdcv2r4e25gjpnvas3m2c6vzpq
Privacy Preserving Data Mining Based on Geometrical Data Transformation Method (GDTM) and K-Means Clustering Algorithm
2018
International Journal of Innovative Computing
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We also propose an improved PPDM that applying Geometrical Data Transformation Method (GDTM) and K-Means Clustering Algorithm for optimum accuracy of mining and zero data loss while preserving the privacy ...
Such problems motivate the research in Privacy Preserving Data Mining (PPDM) and it became one of the newest trends. ...
A work focusing on privacy preserving in K-means clustering by clustering rotation is proposed by [19] . Based on this, data perturbation is employed. The dataset is clustered by K-means clustering. ...
doi:10.11113/ijic.v8n2.174
fatcat:3icxbhdwxrgslcokgf5pbkqb44
Privacy-Preserving Clustering with High Accuracy and Low Time Complexity
[chapter]
2009
Lecture Notes in Computer Science
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This paper proposes an efficient solution with high accuracy to the problem of privacy-preserving clustering. ...
In our research, we focus on the data perturbation approach, and propose an algorithm of linear time complexity based on 1d clustering to perturb the data. ...
In privacy-preserving clustering, a third party data miner requires computing k-means clustering on DB. ...
doi:10.1007/978-3-642-00887-0_40
fatcat:r5niunkbnza6hmbxeokc6tjety
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