Is Data Anonymization an Effective Way to Protect Privacy or Not

This paper examines whether data anonymization is an effective method for protecting personal privacy. With the rapid development of the Internet and artificial intelligence, data has become a key driver of modern societal development, but it also raises ethical and technological challenges regarding privacy protection. Data anonymization protects sensitive data by encrypting it and removing personally identifiable information, aiming to reduce the likelihood of identifying individuals within a dataset. The article analyzes the benefits of data anonymization, including the protection of personal privacy, facilitation of data sharing and transactions, and enhancement of data value utilization, while also highlighting the risks associated with data anonymization, particularly the potential for de-anonymization techniques to re-identify personal data, thereby threatening privacy. The study emphasizes that, despite the risks of data misuse, the rational use of data can bring significant positive value to society. The paper concludes that data anonymization itself is not the problem; the real threat lies in data de-anonymization. To maximize benefits, data anonymization should be used rationally, and risks associated with data de-anonymization should be mitigated through various methods. The article suggests that data collectors should prioritize the protection of sensitive data, and regulatory bodies should strengthen the protection of personal data privacy, adopting technologies such as differential privacy to reduce the risk of data correlation attacks.

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Publication Details

Journal
International Journal of Computer Science and Information Technology
Published
2024-11-24
DOI
https://doi.org/10.62051/ijcsit.v4n3.15
Primary Topic
Privacy, Security, and Data Protection
Type
article
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article

Is Data Anonymization an Effective Way to Protect Privacy or Not

Yiping W. Han, Xiaoping Lü
International Journal of Computer Science and Information Technology
Privacy, Security, and Data Protection
article

Is Data Anonymization an Effective Way to Protect Privacy or Not

Yiping W. Han, Xiaoping Lü
article en

Abstract

This paper examines whether data anonymization is an effective method for protecting personal privacy. With the rapid development of the Internet and artificial intelligence, data has become a key driver of modern societal development, but it also raises ethical and technological challenges regarding privacy protection. Data anonymization protects sensitive data by encrypting it and removing personally identifiable information, aiming to reduce the likelihood of identifying individuals within a dataset. The article analyzes the benefits of data anonymization, including the protection of personal privacy, facilitation of data sharing and transactions, and enhancement of data value utilization, while also highlighting the risks associated with data anonymization, particularly the potential for de-anonymization techniques to re-identify personal data, thereby threatening privacy. The study emphasizes that, despite the risks of data misuse, the rational use of data can bring significant positive value to society. The paper concludes that data anonymization itself is not the problem; the real threat lies in data de-anonymization. To maximize benefits, data anonymization should be used rationally, and risks associated with data de-anonymization should be mitigated through various methods. The article suggests that data collectors should prioritize the protection of sensitive data, and regulatory bodies should strengthen the protection of personal data privacy, adopting technologies such as differential privacy to reduce the risk of data correlation attacks.

International Journal of Computer Science and Information TechnologyVol. 4(3)
Nanjing General Hospital of Nanjing Military Command (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 63%
Privacy, Security, and Data Protection
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Is Data Anonymization an Effective Way to Protect Privacy or Not — Yiping W. Han, Xiaoping Lü · International Journal of Computer Science and Information Technology (2024) | TGRS Research Map | TGRS