THE CHALLENGES OF DE-IDENTIFIED DATA: RE-IDENTIFICATION AND PRIVACY RISKS IN THE DIGITAL AGE

Authors

  • Kerimov Komil Fikratovich Tashkent University of Information Technologies named after Muhammad al-Khwarizmi
  • G‘aniyev Abduxalil Abdujalilovich Tashkent University of Information Technologies named after Muhammad al-Khwarizmi
  • Azizova Zarina Tashkent University of Information Technologies named after Muhammad al-Khwarizmi

Keywords:

data privacy, personal data, data protection, risks, reidentification, deidentification

Abstract

This article discusses the main aspects of personal data and its de-identification as an information protection measure. It also describes the risks of re-identification and the causes of attacks related to this phenomenon and demonstrates the process of collecting, processing and de-identifying personal data.

References

Om, Paul, Broken Promises of Privacy: Responding to the Surprising Failure of Anonymisation (13 August 2009). UCLA Law Review, Vol. 57, p. 1701, 2010, U of Colorado Law Legal Studies Research Paper No. 9-12.

A.A.Ganiev, K.F.Kerimov and Z.I.Azizova, Understanding of Data De-identification: Issues of Relevance and Problems // 2021 International Conference on Information Science and Communications Technologies (ICISCT), 2021, pp. 1-4, doi: 10.1109/ICISCT52966.2021.9670054.

Positive Technologies. Актуальные киберугрозы: II квартал 2023 года – Доступ: https://www.ptsecurity.com/ru-ru/research/analytics/cybersecurity-threatscape-2023-q2.

HIPAA Magazine is the leading provider of news, updates, and independent advice on HIPAA compliance – Режим доступа: https://www.hipaajournal.com/considered-phi-hipaa.

Narayanan, A., Shmatikov, V. (2008). Robust de-anonymization of large sparse datasets. In Proceedings – 2008 IEEE Symposium on Security and Privacy, SP (pp. 111-125).

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Published

2024-02-22

How to Cite

Kerimov, K., G‘aniyev, A., & Azizova, Z. (2024). THE CHALLENGES OF DE-IDENTIFIED DATA: RE-IDENTIFICATION AND PRIVACY RISKS IN THE DIGITAL AGE. DIGITAL TRANSFORMATION AND ARTIFICIAL INTELLIGENCE, 2(1), 33–36. Retrieved from https://dtai.tsue.uz/index.php/dtai/article/view/v2i15