A Comparative Study of Data Anonymization Techniques
Big data; Data privacy; Anonymization; Comparative studies; Data anonymization; Digital era; Personally identifiable information; Privacy preservation; Privacy risks; security; Network security
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| Format: | Conference Paper |
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Institute of Electrical and Electronics Engineers Inc.
2023
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| _version_ | 1833413475175497728 |
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| author | Murthy S. Abu Bakar A. Abdul Rahim F. Ramli R. |
| author2 | 57215129870 |
| author_facet | 57215129870 Murthy S. Abu Bakar A. Abdul Rahim F. Ramli R. |
| author_sort | Murthy S. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Big data; Data privacy; Anonymization; Comparative studies; Data anonymization; Digital era; Personally identifiable information; Privacy preservation; Privacy risks; security; Network security |
| format | Conference Paper |
| id | my.uniten.dspace-24664 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| record_format | dspace |
| spelling | my.uniten.dspace-246642023-05-29T15:25:38Z A Comparative Study of Data Anonymization Techniques Murthy S. Abu Bakar A. Abdul Rahim F. Ramli R. 57215129870 35178991300 57350579500 57191413657 Big data; Data privacy; Anonymization; Comparative studies; Data anonymization; Digital era; Personally identifiable information; Privacy preservation; Privacy risks; security; Network security In today's digital era, it is a very common practice for organizations to collect data from individual users. The collected data is then stored in multiple databases which contain personally identifiable information (PII). This may lead to a major source of privacy risk for the database. Various privacy preservation techniques have been proposed such as perturbation, anonymization and cryptographic. In this study, five anonymization techniques are compared using the same dataset. In addition to that, this study reviews the strengths and weaknesses of the different technique. In the evaluation of efficiency, suppression is found as the most efficient while swapping is in the last place. It is also revealed that swapping is the most resource-consuming technique while suppressing being less resource consuming. � 2019 IEEE. Final 2023-05-29T07:25:38Z 2023-05-29T07:25:38Z 2019 Conference Paper 10.1109/BigDataSecurity-HPSC-IDS.2019.00063 2-s2.0-85072765291 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072765291&doi=10.1109%2fBigDataSecurity-HPSC-IDS.2019.00063&partnerID=40&md5=0cff5e2b3819a6818d170d011b623056 https://irepository.uniten.edu.my/handle/123456789/24664 8819477 306 309 Institute of Electrical and Electronics Engineers Inc. Scopus |
| spellingShingle | Murthy S. Abu Bakar A. Abdul Rahim F. Ramli R. A Comparative Study of Data Anonymization Techniques |
| title | A Comparative Study of Data Anonymization Techniques |
| title_full | A Comparative Study of Data Anonymization Techniques |
| title_fullStr | A Comparative Study of Data Anonymization Techniques |
| title_full_unstemmed | A Comparative Study of Data Anonymization Techniques |
| title_short | A Comparative Study of Data Anonymization Techniques |
| title_sort | comparative study of data anonymization techniques |
| url_provider | http://dspace.uniten.edu.my/ |