Fuzz-classification (p, l)-Angel: An enhanced hybrid artificial intelligence based fuzzy logic for multiple sensitive attributes against privacy breaches
Journal article
Authors | Kanwal, 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. |
Keywords | Generalization; Fuzzy-logic; Multiple Sensitive Attributes (MSA); Privacy disclosures ; Membership function |
Year | 2022 |
Journal | Elsevier Digital Communications and Networks |
Journal citation | pp. 1-16 |
Publisher | Elseiver |
ISSN | 2352-8648 |
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 status | Published |
Publication dates | |
Online | 12 Oct 2022 |
Publication process dates | |
Accepted | 29 Sep 2022 |
Deposited | 16 Dec 2022 |
https://repository.derby.ac.uk/item/9vy93/fuzz-classification-p-l-angel-an-enhanced-hybrid-artificial-intelligence-based-fuzzy-logic-for-multiple-sensitive-attributes-against-privacy-breaches
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License: CC BY-NC-ND | ||
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