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A conceptual anonymity model to ensure privacy for sensitive network data

In today's world, a great amount of people, devices, and sensors are well connected through various online platforms, and the interactions between these entities produce massive amounts of useful information. This process of data production and sharing appears to be on the rise. The growing pop...

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Main Authors:	Arafat, N.H.M., Pramanik, Md Ileas, Abu Jafar, Md Muzahid, Lu, Bibo, Jahan, Sumaiya, Murad, Saydul Akbar
Format:	Conference or Workshop Item
Language:	English English
Published:	Institute of Electrical and Electronics Engineers Inc. 2021
Subjects:	QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/42380/1/A%20conceptual%20anonymity%20model%20to%20ensure%20privacy.pdf http://umpir.ump.edu.my/id/eprint/42380/2/A%20conceptual%20anonymity%20model%20to%20ensure%20privacy%20for%20sensitive%20network%20data_ABS.pdf http://umpir.ump.edu.my/id/eprint/42380/ https://doi.org/10.1109/ETCCE54784.2021.9689791
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spelling	my.ump.umpir.423802024-10-30T04:38:03Z http://umpir.ump.edu.my/id/eprint/42380/ A conceptual anonymity model to ensure privacy for sensitive network data Arafat, N.H.M. Pramanik, Md Ileas Abu Jafar, Md Muzahid Lu, Bibo Jahan, Sumaiya Murad, Saydul Akbar QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) In today's world, a great amount of people, devices, and sensors are well connected through various online platforms, and the interactions between these entities produce massive amounts of useful information. This process of data production and sharing appears to be on the rise. The growing popularity of this industry, as well as the required development of data sharing tools and technology, pose major threats to an individual's sensitive information privacy. These privacy-related issues may elicit a regularly strong negative reaction and restrain further organizational invention. Researchers have identified the privacy implications of large data collections and contributed to the preservation of data from unauthorised exposure to solve the challenge of information privacy. However, the majority of privacy strategies concentrate solely on traditional data models, such as micro-data. The academe and industry are paying more attention to network data privacy challenges. In this paper, we offer (ℓ, k)-anonymity, a novel privacy paradigm for network data that focuses on maintaining the privacy of both node and link information. Here, original network data will turn to attribute generalization nodes through a complex process, where several algorithms, clustering, node generalization, link generalization and ℓ-diversification will be applied. As a result, (ℓ, k)-anonymous network will be generated and will filter original network data to ensure publishable (ℓ, k)-anonymize data. Hopefully, this anonymity model will have a stronger role against homogeneity attacks of intruders, which will prevent the unauthorized disclosure of sensitive network data for several areas, such as - health sector. This model will also be cost effective and data loss will be controlled using two different ways. Institute of Electrical and Electronics Engineers Inc. 2021 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/42380/1/A%20conceptual%20anonymity%20model%20to%20ensure%20privacy.pdf pdf en http://umpir.ump.edu.my/id/eprint/42380/2/A%20conceptual%20anonymity%20model%20to%20ensure%20privacy%20for%20sensitive%20network%20data_ABS.pdf Arafat, N.H.M. and Pramanik, Md Ileas and Abu Jafar, Md Muzahid and Lu, Bibo and Jahan, Sumaiya and Murad, Saydul Akbar (2021) A conceptual anonymity model to ensure privacy for sensitive network data. In: 2021 Emerging Technology in Computing, Communication and Electronics, ETCCE 2021. 2021 Emerging Technology in Computing, Communication and Electronics, ETCCE 2021 , 21 - 23 December 2021 , Dhaka. pp. 1-7.. ISBN 978-166548364-3 (Published) https://doi.org/10.1109/ETCCE54784.2021.9689791
institution	Universiti Malaysia Pahang Al-Sultan Abdullah
building	UMPSA Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Pahang Al-Sultan Abdullah
content_source	UMPSA Institutional Repository
url_provider	http://umpir.ump.edu.my/
language	English English
topic	QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General)
spellingShingle	QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) Arafat, N.H.M. Pramanik, Md Ileas Abu Jafar, Md Muzahid Lu, Bibo Jahan, Sumaiya Murad, Saydul Akbar A conceptual anonymity model to ensure privacy for sensitive network data
description	In today's world, a great amount of people, devices, and sensors are well connected through various online platforms, and the interactions between these entities produce massive amounts of useful information. This process of data production and sharing appears to be on the rise. The growing popularity of this industry, as well as the required development of data sharing tools and technology, pose major threats to an individual's sensitive information privacy. These privacy-related issues may elicit a regularly strong negative reaction and restrain further organizational invention. Researchers have identified the privacy implications of large data collections and contributed to the preservation of data from unauthorised exposure to solve the challenge of information privacy. However, the majority of privacy strategies concentrate solely on traditional data models, such as micro-data. The academe and industry are paying more attention to network data privacy challenges. In this paper, we offer (ℓ, k)-anonymity, a novel privacy paradigm for network data that focuses on maintaining the privacy of both node and link information. Here, original network data will turn to attribute generalization nodes through a complex process, where several algorithms, clustering, node generalization, link generalization and ℓ-diversification will be applied. As a result, (ℓ, k)-anonymous network will be generated and will filter original network data to ensure publishable (ℓ, k)-anonymize data. Hopefully, this anonymity model will have a stronger role against homogeneity attacks of intruders, which will prevent the unauthorized disclosure of sensitive network data for several areas, such as - health sector. This model will also be cost effective and data loss will be controlled using two different ways.
format	Conference or Workshop Item
author	Arafat, N.H.M. Pramanik, Md Ileas Abu Jafar, Md Muzahid Lu, Bibo Jahan, Sumaiya Murad, Saydul Akbar
author_facet	Arafat, N.H.M. Pramanik, Md Ileas Abu Jafar, Md Muzahid Lu, Bibo Jahan, Sumaiya Murad, Saydul Akbar
author_sort	Arafat, N.H.M.
title	A conceptual anonymity model to ensure privacy for sensitive network data
title_short	A conceptual anonymity model to ensure privacy for sensitive network data
title_full	A conceptual anonymity model to ensure privacy for sensitive network data
title_fullStr	A conceptual anonymity model to ensure privacy for sensitive network data
title_full_unstemmed	A conceptual anonymity model to ensure privacy for sensitive network data
title_sort	conceptual anonymity model to ensure privacy for sensitive network data
publisher	Institute of Electrical and Electronics Engineers Inc.
publishDate	2021
url	http://umpir.ump.edu.my/id/eprint/42380/1/A%20conceptual%20anonymity%20model%20to%20ensure%20privacy.pdf http://umpir.ump.edu.my/id/eprint/42380/2/A%20conceptual%20anonymity%20model%20to%20ensure%20privacy%20for%20sensitive%20network%20data_ABS.pdf http://umpir.ump.edu.my/id/eprint/42380/ https://doi.org/10.1109/ETCCE54784.2021.9689791
_version_	1822924727087267840
score	13.234278

A conceptual anonymity model to ensure privacy for sensitive network data

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