Blockchain Universal Data Privacy Protection Method Supporting K-Nearest Neighbor Search
With the continuous expansion of blockchain universal data application scenarios,it involves more and more data privacy.Data privacy leakage may lead to personal credit damage,property losses,and even identity theft.Reasonable and efficient protection of user identity information and data privacy is a key issue in ensuring the security of blockchain universal data.To this end,a blockchain universal data privacy protection method that supports K-nearest neighbor search has been proposed.Collect blockchain universal data,use k-prototypes algorithm to cluster blockchain universal data,and control classification and numerical attributes.On this basis,this article supports K-nearest neighbor search,establishes a blockchain universal data system model,identifies sensitive areas of blockchain universal data,and achieves blockchain universal data privacy protection.The experimental results show that the proposed method has a good effect on blockchain universal data privacy protection,can effectively improve the security of blockchain universal data privacy protection,and shorten the time for blockchain universal data privacy protection.
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