TARU PUBLICATIONS
Journal of Discrete Mathematical Sciences and Cryptography cover
Open Access ·Peer-reviewed·ISSN (Online): 2169-0065·ISSN (Print): 0972-0529

Monthly Journal: Publishes theoretical and applied research in all areas of Discrete Mathematical Sciences, Cryptography, Combinatorics, Elliptic Curves and Information Security.

Issues up to 2022 co-published with and available at:Taylor & Francis Online
submissions@tarupublications.com
Open Access Research Article

Secure data sharing in collaborative network environments for privacy-preserving mechanisms

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* Corresponding author · click or hover a name for details

pp. 855–865Vol. 27Issue 2-BMarch 2024DOI: 10.47974/JDMSC-1961 Crossmark XML
Published Online:
12 Apr 2024
Article type:
Research Article
Language:
EN
Article no.:
JDMSC-1961
Pages:
855–865

Abstract

In today’s world where everything is linked, shared network settings are necessary to share info between companies. However, making sure that data is safe and private in these kinds of settings is very hard. This paper describes a new way to share data safely, focusing on privacy-protecting features that keep private data safe while making it easier for people to work together.To keep data safe at different steps of sharing and processing, the suggested answer uses a mix of cryptography, access controls, and anonymization techniques. Unauthorized access is stopped and privacy is kept by encrypting data both while it is being sent and while it is being stored. Access controls are also used to make sure that only people who are allowed to can see or change private data. These controls are based on rules that have already been set. Also, methods like differential privacy are used to make privacy even better by adding noise to question results. This stops individual records from being identified while still allowing useful analysis. Together, these methods make it possible to share data safely and privately, which encourages cooperation without jeopardizing accuracy or privacy.Overall, this method provides a complete framework for dealing with the tricky issues of data security and privacy in collaborative network settings. It lets businesses share information freely while still following strict privacy rules and keeping private data from getting into the wrong hands or being shared without permission.

Keywords

Subject Classifications

68M25

References

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