Classification of data anonymization techniques
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Tarih
2025
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
CRC Press
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In a world where data is becoming more valuable, finding new ways to keep our privacy safe against the tide of tech progress is more important than ever. This chapter dives deep into the world of anonymizing data in plain sight, blending deep thought with real-world uses, especially when it comes to the innovative industries of today and digital security. The chapter delves into the entire realm of data anonymization, encompassing basic techniques such as masking and expanding data, as well as intricate methods such as mathematically guaranteeing privacy and encrypting data while maintaining its usability. The discussion also focuses on how artificial intelligence (AI) is changing the game, making data anonymization more accessible. When talking about the new industrial revolution, it highlights how crucial AI is for making things run smoothly, from the Internet of Things to factories of the future, all while keeping our digital selves under wraps. Moreover, the chapter walks through the minefield of moral and legal rules, stressing the double challenge of following laws like the General Data Protection Regulation and California Consumer Privacy Act and the moral duty to keep individual privacy intact. It thoughtfully weighs the balance between keeping privacy sacred and making the most of data for the good of society and business. This key piece of work weaves together the theory and practice of making data anonymous, shining a spotlight on the vital role of AI and the need to keep evolving to meet the privacy challenges of our digital age. It sets the stage for more studies, policymaking, and ethical discussions on keeping our data safe, showing just how essential these strategies are in our data-soaked world.
Açıklama
Anahtar Kelimeler
data anonymization techniques
Kaynak
Artificial Intelligence for Cyber Security and Industry 4.0
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Koyuncu, H., & Altaher, R. (2025). Classification of data anonymization techniques. In Artificial Intelligence for Cyber Security and Industry 4.0. CRC Press, 57-96. 10.1201/9781032657264-3
