Title:

Improved Association Rule Mining-Based Data Sanitization for Privacy Preservation Model in Cloud, Journal of Telecommunications and Information Technology, 2023, nr 1

Group publication title:

2023, nr 1, JTIT-artykuły

Creator:

HimaBindu, Gottumukkala ; Patil, Rajkumar

Subject and Keywords:

data security ; sanitization ; improved apriori ; modified data restoration

Description:

Data security in cloud services is achieved by imposing a broad range of privacy settings and restrictions. However, the different security techniques used fail to eliminate the hazard of serious data leakage, information loss and other vulnerabilities. Therefore, better security policy requirements are necessary to ensure acceptable data protection levels in the cloud. The two procedures presented in this paper are intended to build a new cloud data security method. Here, sensitive data stored in big datasets is protected from abuse via the data sanitization procedure relying on an improved apriori approach to clean the data. The main objective in this case is to generate a key using an optimization technique known as Corona-integrated Archimedes Optimization with Tent Map Estimation (CIAO-TME). Such a technique deals with both restoration and sanitization of data. The problem of optimizing the data preservation ratio (IPR), the hiding ratio (HR), and the degree of modification (DOM) is formulated and researched as well.

Publisher:

Instytut Łączności - Państwowy Instytut Badawczy

Date:

2023, nr 1

Resource Type:

artykuł

Format:

application/pdf

Resource Identifier:

ISSN 1509-4553, on-line: ISSN 1899-8852

DOI:

10.26636/jtit.2023.166922

eISSN:

1899-8852

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności