An Enterprise Data Privacy Governance Model: Security-Centric Multi-Model Data Anonymization

Year 2023, Volume: 15 Issue: 2, 574 - 583, 14.07.2023

Yağmur Şahin , İbrahim Dogru

https://doi.org/10.29137/umagd.1272085

Cited By: 1

Abstract

The increasing need for data privacy and the rising complexity of data environments necessitate robust data anonymization techniques to safeguard personal and sensitive information. A multi-model approach to data anonymization can strike an optimal balance between privacy protection and data utility, integrating techniques such as data masking, differential privacy, machine learning algorithms, blockchain technology, and data encryption. This article introduces a Security-Centric Enterprise Data Anonymization Governance Model, a structured framework for managing data privacy across healthcare, finance, and government industries. The model ensures adherence to best practices and compliance with legal and regulatory requirements. The article addresses challenges in implementing data anonymization techniques, including maintaining data utility and preventing re-identification, by advocating for a multi-model approach that combines various technologies and methods. We suggest that by adopting this holistic approach, organizations can enhance their data protection measures and foster a culture of data privacy.

Keywords

data privacy, data anonymization, multi-model approach, data utility, data governance

Bir Kurumsal Veri Gizlilik Yönetişim Modeli: Güvenlik-Merkezli Çoklu Model Veri Anonimleştirme

Abstract

Veri gizliliği ihtiyacının artması ve veri ortamlarının karmaşıklığının yükselmesi, kişisel ve hassas bilgileri korumak için güçlü veri anonimleştirme tekniklerini zorunlu kılmıştır. Çoklu model yaklaşımı ile veri anonimleştirmeye dair, veri gizlilik koruması ve veri kullanılabilirliği arasında optimal bir denge sağlamak mümkündür. Bu yaklaşım, veri maskesi, diferansiyel gizlilik, makine öğrenimi algoritmaları, blockchain teknolojisi ve veri şifreleme gibi teknikleri bir araya getirerek sağlık, finans ve devlet sektörlerine yönelik veri gizliliğini yönetmek için yapılandırılmış bir çerçeve olan Güvenlik-Merkezli Kurumsal Veri Anonimleştirme Yönetişim Modeli'ni sunmaktadır. Model, yasal ve düzenleyici gerekliliklere uyumu güvence altına alacak şekilde tasarlanmıştır. Makale, veri anonimleştirme tekniklerinin uygulanmasındaki zorlukları, veri kullanılabilirliğini sürdürme ve yeniden tanımlamayı önleme gibi konuları ele alarak, çeşitli teknolojileri ve yöntemleri birleştiren çoklu model yaklaşımını savunmaktadır. Makalede bu bütüncül yaklaşımı benimseyerek kuruluşların veri koruma önlemlerini artırabileceği ve veri gizliliği kültürünü destekleyebileceği öne sürülmektedir.

Keywords

Veri gizliliği, veri anonimleştirme, çoklu model yaklaşımı, veri kullanılabilirliği, veri yönetişimi

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