Abstract
The mainstream technology of recent years is big data which leads to security and privacy concerns. Every individual has a right to preserve his information private and should not be revealed in any way. The wide range of actors like businesses, government, NGOs, etc., are helping in the collection of huge data, storing it, analyzing it, and then sharing it with end users for the purpose of data analytics. Thus the privacy preservation becomes very significant before publishing the data for open use. The data publishing depends on various rules, government policies, and guidelines wherein published data reveal only the required information based on the agreements. Thus, we can consider privacy preservation and publishing of data as a tool that has many methods for preserving privacy of the records before publishing it. Data anonymization technique before publishing of data promotes open use of data for analysis along with ensuring the private information privacy of individuals. This paper analyzes different anonymization methods and algorithms and provides detailed comparison of them on important parameters.
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Madan, S. (2020). A Literature Analysis on Privacy Preservation Techniques. In: Sharma, H., Govindan, K., Poonia, R., Kumar, S., El-Medany, W. (eds) Advances in Computing and Intelligent Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-0222-4_19
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