Improved Association Rule Mining-Based Data Sanitization for Privacy Preservation Model in Cloud

• Autorzy: Patil Rajkumar , HimaBindu Gottumukkala

Identyfikatory

DOI

10.26636/jtit.2023.166922

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

data security; improved apriori; modified data restoration; sanitization

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2023
• Tom: nr 1
• Strony: 51--59
• Opis fizyczny: Bibliogr. 31 poz., rys., tab.

Twórcy

autor

Patil Rajkumar

• Department of Computer Science Engineering, GITAM (Deemed to be) University, Hyderabad, Telangana, India

autor

HimaBindu Gottumukkala

• Department of Computer Science Engineering, GITAM (Deemed to be) University, Hyderabad, Telangana, India

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).