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- W4312271702 abstract "An intelligent security model for the big data environment is presented in this paper. The proposed security framework is data sensitive in nature and the level of security offered is defined on the basis of the data secrecy standard. The application area preferred in this work is the healthcare sector where the amount of data generated through the digitization and aggregation of medical equipment's readings and reports is huge. Security and privacy of this data is also a very important aspect in healthcare sector and has been incorporated in the healthcare act of many countries. However, the security level implemented conventionally is of same level to the complete data which not a smart strategy considering the varying level of sensitivity of data. It is inefficient for the data of high sensitivity and redundant for the data of low sensitivity. An intelligent data sensitive security framework is therefore proposed in this paper which provides the security level best suited for the data of given sensitivity. Fuzzy logic decision making technique is used in this work to determine the security level for a respective sensitivity level. Various patient attributes are used to take the intelligent decision about the security level through fuzzy inference system. The effectiveness and the efficacy of the proposed work is verified through the experimental study." @default.
- W4312271702 created "2023-01-04" @default.
- W4312271702 creator A5050694980 @default.
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- W4312271702 date "2022-01-01" @default.
- W4312271702 modified "2023-10-17" @default.
- W4312271702 title "Intelligent data sensitive security model for big data in the healthcare using fuzzy logic" @default.
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- W4312271702 doi "https://doi.org/10.1063/5.0106426" @default.
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