Next Article in Journal
Secure and Efficient High Throughput Medium Access Control for Vehicular Ad-Hoc Network
Previous Article in Journal
Learning Carbohydrate Digestion and Insulin Absorption Curves Using Blood Glucose Level Prediction and Deep Learning Models
Previous Article in Special Issue
Deep Neural Network Sleep Scoring Using Combined Motion and Heart Rate Variability Data
 
 
Article

F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes

1
Department of Computer Sciences, COMSATS University, Islamabad 45550, Pakistan
2
Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
3
Cybernetica AS, 12618 Tallinn, Estonia
4
Department of Computer Science, Edge Hill University, Lancashire L39 4QP, UK
5
James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK
6
College of Engineering and IT, Ajman University, Ajman 20550, United Arab Emirates
7
Artificial Intelligence Research Centre (AIRC), Ajman University, Ajman 20550, United Arab Emirates
*
Author to whom correspondence should be addressed.
Academic Editor: Rebeca P. Díaz Redondo
Sensors 2021, 21(14), 4933; https://doi.org/10.3390/s21144933
Received: 6 April 2021 / Revised: 5 July 2021 / Accepted: 6 July 2021 / Published: 20 July 2021
(This article belongs to the Special Issue Sensing and Data Analysis Techniques for Intelligent Healthcare)
With the advent of smart health, smart cities, and smart grids, the amount of data has grown swiftly. When the collected data is published for valuable information mining, privacy turns out to be a key matter due to the presence of sensitive information. Such sensitive information comprises either a single sensitive attribute (an individual has only one sensitive attribute) or multiple sensitive attributes (an individual can have multiple sensitive attributes). Anonymization of data sets with multiple sensitive attributes presents some unique problems due to the correlation among these attributes. Artificial intelligence techniques can help the data publishers in anonymizing such data. To the best of our knowledge, no fuzzy logic-based privacy model has been proposed until now for privacy preservation of multiple sensitive attributes. In this paper, we propose a novel privacy preserving model F-Classify that uses fuzzy logic for the classification of quasi-identifier and multiple sensitive attributes. Classes are defined based on defined rules, and every tuple is assigned to its class according to attribute value. The working of the F-Classify Algorithm is also verified using HLPN. A wide range of experiments on healthcare data sets acknowledged that F-Classify surpasses its counterparts in terms of privacy and utility. Being based on artificial intelligence, it has a lower execution time than other approaches. View Full-Text
Keywords: DCP; F-Classify; membership function; MSA; MST; (p, k) angelization; QT DCP; F-Classify; membership function; MSA; MST; (p, k) angelization; QT
Show Figures

Figure 1

MDPI and ACS Style

Attaullah, H.; Anjum, A.; Kanwal, T.; Malik, S.U.R.; Asheralieva, A.; Malik, H.; Zoha, A.; Arshad, K.; Imran, M.A. F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes. Sensors 2021, 21, 4933. https://doi.org/10.3390/s21144933

AMA Style

Attaullah H, Anjum A, Kanwal T, Malik SUR, Asheralieva A, Malik H, Zoha A, Arshad K, Imran MA. F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes. Sensors. 2021; 21(14):4933. https://doi.org/10.3390/s21144933

Chicago/Turabian Style

Attaullah, Hasina, Adeel Anjum, Tehsin Kanwal, Saif Ur Rehman Malik, Alia Asheralieva, Hassan Malik, Ahmed Zoha, Kamran Arshad, and Muhammad Ali Imran. 2021. "F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes" Sensors 21, no. 14: 4933. https://doi.org/10.3390/s21144933

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop