A hybrid-security model for privacy-enhanced distributed data mining
This study encompasses the proposal of a novel hybrid-security model that incorporates the benefits of both the centralised data mining system as well the distributed data mining system. The hybrid model provides two levels of security. The first security level perturbs the individual datasets by tr...
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| Format: | Article |
| Language: | English |
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Springer
2022-06-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157820304109 |
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| author | Tanzeela Javid Manoj Kumar Gupta Abhishek Gupta |
| author_facet | Tanzeela Javid Manoj Kumar Gupta Abhishek Gupta |
| author_sort | Tanzeela Javid |
| collection | DOAJ |
| description | This study encompasses the proposal of a novel hybrid-security model that incorporates the benefits of both the centralised data mining system as well the distributed data mining system. The hybrid model provides two levels of security. The first security level perturbs the individual datasets by transforming it into a non-understandable form using the four-dimensional rotation transformation, and the second security level helps in performing secure distributed data mining using the ratio of secure summation protocol. The trivial data mining techniques, such as k-means clustering technique and naïve Bayes classification technique, verifies the efficiency and accuracy of the hybrid security model. The hybrid security model provides security to sensitive data without compromising the quality of the data. The accuracy obtained in classification task and clustering task using naïve Bayes and k-means technique is high when different datasets in a privacy-enhanced distributed data mining environment verify the working of the hybrid security model. |
| format | Article |
| id | doaj-art-41e49ece90cf42c69a24cbf3f13b5fa5 |
| institution | Kabale University |
| issn | 1319-1578 |
| language | English |
| publishDate | 2022-06-01 |
| publisher | Springer |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj-art-41e49ece90cf42c69a24cbf3f13b5fa52025-08-20T03:48:35ZengSpringerJournal of King Saud University: Computer and Information Sciences1319-15782022-06-013463602361410.1016/j.jksuci.2020.06.010A hybrid-security model for privacy-enhanced distributed data miningTanzeela Javid0Manoj Kumar Gupta1Abhishek Gupta2Corresponding author.; Department of Computer Science and Engineering, Shri Mata Vaishno Devi University Katra, Jammu and Kashmir, IndiaDepartment of Computer Science and Engineering, Shri Mata Vaishno Devi University Katra, Jammu and Kashmir, IndiaDepartment of Computer Science and Engineering, Shri Mata Vaishno Devi University Katra, Jammu and Kashmir, IndiaThis study encompasses the proposal of a novel hybrid-security model that incorporates the benefits of both the centralised data mining system as well the distributed data mining system. The hybrid model provides two levels of security. The first security level perturbs the individual datasets by transforming it into a non-understandable form using the four-dimensional rotation transformation, and the second security level helps in performing secure distributed data mining using the ratio of secure summation protocol. The trivial data mining techniques, such as k-means clustering technique and naïve Bayes classification technique, verifies the efficiency and accuracy of the hybrid security model. The hybrid security model provides security to sensitive data without compromising the quality of the data. The accuracy obtained in classification task and clustering task using naïve Bayes and k-means technique is high when different datasets in a privacy-enhanced distributed data mining environment verify the working of the hybrid security model.http://www.sciencedirect.com/science/article/pii/S1319157820304109Privacy-enhanced data miningFour-dimensional rotation transformationRatio of secure summationHybrid privacy-enhanced data mining model |
| spellingShingle | Tanzeela Javid Manoj Kumar Gupta Abhishek Gupta A hybrid-security model for privacy-enhanced distributed data mining Journal of King Saud University: Computer and Information Sciences Privacy-enhanced data mining Four-dimensional rotation transformation Ratio of secure summation Hybrid privacy-enhanced data mining model |
| title | A hybrid-security model for privacy-enhanced distributed data mining |
| title_full | A hybrid-security model for privacy-enhanced distributed data mining |
| title_fullStr | A hybrid-security model for privacy-enhanced distributed data mining |
| title_full_unstemmed | A hybrid-security model for privacy-enhanced distributed data mining |
| title_short | A hybrid-security model for privacy-enhanced distributed data mining |
| title_sort | hybrid security model for privacy enhanced distributed data mining |
| topic | Privacy-enhanced data mining Four-dimensional rotation transformation Ratio of secure summation Hybrid privacy-enhanced data mining model |
| url | http://www.sciencedirect.com/science/article/pii/S1319157820304109 |
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