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Big Data analytics for privacy through ND-homomorphic encryption
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作者 S.Saravanan n.poornima 《Journal of Control and Decision》 EI 2023年第1期64-71,共8页
Rapidly rising the quantity of Big Data is an opportunity to flout the privacy of people. Whenhigh processing capacity and massive storage are required for Big Data, distributed networkshave been used. There are sever... Rapidly rising the quantity of Big Data is an opportunity to flout the privacy of people. Whenhigh processing capacity and massive storage are required for Big Data, distributed networkshave been used. There are several people involved in these activities, the system may contributeto privacy infringements frameworks have been developed for the preservation of privacy atvarious levels (e.g. information age, information the executives and information preparing) asfor the existing pattern of huge information. We plan to frame this paper as a literature surveyof these classifications, including the Privacy Processes in Big Data and the presentation of theAssociate Challenges. Homomorphic encryption is particularised aimed at solitary single actionon the ciphered information. Homomorphic enciphering is restrained to an honest operation onthe encoded data. The reference to encryption project fulfils many accurate trading operationson coded numerical data;therefore, it protects the written in code-sensible information evenmore. 展开更多
关键词 Security and confidentiality vast statistics data ENCRYPTION nondeterministic fully homomorphic encryption
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