Abstract
Data Anonymization is the process of irreversibly hiding data in obscurity. There are many methods to hide certain parts of data such as names, phone numbers, passwords, credit card info, etc. In an educational setting, we’re mostly focusing on anonymizing students’ names on test results so no one’s identity is compromised. I have looked at studies describing the possibility of publication of students’ data, in secondary school success, state graduation exam scores, and success during their first year of university study for analyses, to colleges. In order to find data patterns and relationships by using data mining techniques, the data must be released in the form called original tuples, instead of pre-aggregated statistics. These records contain sensitive and even important personal information, which has implied significant privacy concerns regarding the disclosure of such data. I felt very curious and passionate about researching this topic because of the results I had come across. These results explained to me the different algorithms used in Data Anonymization and how it’s applied. The algorithms are very similar to the methods I’ve researched in the past.
How to Cite:
, A. & , M.,
(2022) “What type of Data Anonymization Methods Will Help Give Us Better Results in an Educational Setting?”,
Journal of Student-Scientists' Research 4.
doi: https://doi.org/10.13021/jssr2022.3385
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