Heap Bucketization Anonymity—An Efficient Privacy-Preserving Data Publishing Model for Multiple Sensitive Attributes-Reference-Cited by-同舟云学术

Heap Bucketization Anonymity—An Efficient Privacy-Preserving Data Publishing Model for Multiple Sensitive Attributes

Published:2022 Issue: Volume:10 Page:28773-28791
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Jayapradha J.¹^ORCID,Prakash M.²^ORCID,Alotaibi Youseef³^ORCID,Khalaf Osamah Ibrahim⁴^ORCID,Alghamdi Saleh Ahmed⁵

Affiliation:

1. Department of Computing Technologies, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India

2. Department of Data Science and Business Systems, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India

3. Department of Computer Science, College of Computer and Information Systems, Umm Al-Qura University, Makkah, Saudi Arabia

4. Al-Nahrain Nanorenewable Energy Research Center, Al-Nahrain University, Baghdad, Iraq

5. Department of Information Technology, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia

Funder

Taif University through the Taif University Researchers Supporting Project, Taif University, Taif, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09732456.pdf?arnumber=9732456

Reference66 articles.

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4. Privacy-preserving data publishing for multiple numerical sensitive attributes;liu;Tsinghua Sci Technol,2015

5. Preserving privacy for sensitive values of individuals in data publishing based on a new additive noise approach;zhu;Proc 23rd Int Conf Comput Commun Netw (ICCCN),2014

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