This page has only limited features, please log in for full access.

Unclaimed
Hasina Attaullah
Department of Computer Sciences, COMSATS University, Islamabad 45550, Pakistan

Basic Info

Basic Info is private.

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 20 July 2021 in Sensors
Reads 0
Downloads 0

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.

ACS Style

Hasina Attaullah; Adeel Anjum; Tehsin Kanwal; Saif Malik; Alia Asheralieva; Hassan Malik; Ahmed Zoha; Kamran Arshad; Muhammad Imran. F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes. Sensors 2021, 21, 4933 .

AMA Style

Hasina Attaullah, Adeel Anjum, Tehsin Kanwal, Saif Malik, Alia Asheralieva, Hassan Malik, Ahmed Zoha, Kamran Arshad, Muhammad Imran. F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes. Sensors. 2021; 21 (14):4933.

Chicago/Turabian Style

Hasina Attaullah; Adeel Anjum; Tehsin Kanwal; Saif Malik; Alia Asheralieva; Hassan Malik; Ahmed Zoha; Kamran Arshad; Muhammad Imran. 2021. "F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes." Sensors 21, no. 14: 4933.