Fuzz-classification (p, l)-Angel: An enhanced hybrid artificial intelligence based fuzzy logic for multiple sensitive attributes against privacy breaches

Journal article


Kanwal, T., Attaullaha, H., Anjum, A., Khan, A. and Jeon, G. 2022. Fuzz-classification (p, l)-Angel: An enhanced hybrid artificial intelligence based fuzzy logic for multiple sensitive attributes against privacy breaches. Elsevier Digital Communications and Networks. pp. 1-16. https://doi.org/10.1016/j.dcan.2022.09.025
AuthorsKanwal, T., Attaullaha, H., Anjum, A., Khan, A. and Jeon, G.
Abstract

The inability of traditional privacy-preserving models to protect multiple datasets based on sensitive attributes has prompted researchers to propose models such as SLOMS, SLAMSA, (p, k)-Angelization, and (p, l)-Angelization, but these were found to be insufficient in terms of robust privacy and performance. (p, l)-Angelization was successful against different privacy disclosures, but it was not efficient. To the best of our knowledge, no robust privacy model based on fuzzy logic has been proposed to protect the privacy of sensitive attributes with multiple records. In this paper, we suggest an improved version of (p, l)-Angelization based on a hybrid AI approach and privacy-preserving approach like Generalization. Fuzz-classification (p, l)-Angel uses artificial intelligence based fuzzy logic for classification, a high-dimensional segmentation technique for segmenting quasi-identifiers and multiple sensitive attributes. We demonstrate the feasibility of the proposed solution by modelling and analyzing privacy violations using High-Level Petri Nets. The results of the experiment demonstrate that the proposed approach produces better results in terms of efficiency and utility.

KeywordsGeneralization; Fuzzy-logic; Multiple Sensitive Attributes (MSA); Privacy disclosures ; Membership function
Year2022
JournalElsevier Digital Communications and Networks
Journal citationpp. 1-16
PublisherElseiver
ISSN2352-8648
Digital Object Identifier (DOI)https://doi.org/10.1016/j.dcan.2022.09.025
Web address (URL)https://www.sciencedirect.com/science/article/pii/S2352864822002000
Accepted author manuscript
File Access Level
Open
Publisher's version
License
File Access Level
Open
Output statusPublished
Publication dates
Online12 Oct 2022
Publication process dates
Accepted29 Sep 2022
Deposited16 Dec 2022
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File access level: Open


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License: CC BY 4.0
File access level: Open

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