A Study of Big Data Security on a Partitional Clustering Algorithm with Perturbation Technique
Partitional Clustering Algorithm (PCA) on the Hadoop Distributed File System is to perform big data securities using the Perturbation Technique is the main idea of the proposed work. There are numerous clustering methods available that are used to categorize the information from the big data. PCA di...
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| Vydáno v: | 2020 International Conference on Smart Electronics and Communication (ICOSEC) s. 482 - 486 |
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| Jazyk: | angličtina |
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01.09.2020
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| Abstract | Partitional Clustering Algorithm (PCA) on the Hadoop Distributed File System is to perform big data securities using the Perturbation Technique is the main idea of the proposed work. There are numerous clustering methods available that are used to categorize the information from the big data. PCA discovers the cluster based on the initial partition of the data. In this approach, it is possible to develop a security safeguarding of data that is impoverished to allow the calculations and communication. The performances were analyzed on Health Care database under the studies of various parameters like precision, accuracy, and F-score measure. The outcome of the results is to demonstrate that this method is used to decrease the complication in preserving privacy and better accuracy than that of the existing techniques. |
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| AbstractList | Partitional Clustering Algorithm (PCA) on the Hadoop Distributed File System is to perform big data securities using the Perturbation Technique is the main idea of the proposed work. There are numerous clustering methods available that are used to categorize the information from the big data. PCA discovers the cluster based on the initial partition of the data. In this approach, it is possible to develop a security safeguarding of data that is impoverished to allow the calculations and communication. The performances were analyzed on Health Care database under the studies of various parameters like precision, accuracy, and F-score measure. The outcome of the results is to demonstrate that this method is used to decrease the complication in preserving privacy and better accuracy than that of the existing techniques. |
| Author | Natarajan, V. Marichamy, V. Santhana |
| Author_xml | – sequence: 1 givenname: V. Santhana surname: Marichamy fullname: Marichamy, V. Santhana organization: SRM Valliammai Engineering College,Department of Computer Applications,Kattankulathur,India,603203 – sequence: 2 givenname: V. surname: Natarajan fullname: Natarajan, V. organization: Anna University, MIT Campus,Department of Instrumentation Engineering,Chrompet,Chennai,India,600044 |
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| Snippet | Partitional Clustering Algorithm (PCA) on the Hadoop Distributed File System is to perform big data securities using the Perturbation Technique is the main... |
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| SubjectTerms | Accuracy Big Data Clustering algorithms Clustering Tme Conferences Execution Time F-Socre Measure HDFS Partitioning algorithms PCA Perturbation methods Precision Principal component analysis Privacy Preserving Security |
| Title | A Study of Big Data Security on a Partitional Clustering Algorithm with Perturbation Technique |
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