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This fully homomorphic encryption method allows for users of cloud storage platforms to retrieve encrypted information or data without having first to decrypt the data, reducing the risk of exposing sensitive data. Hackers have broken into preexisting encrypted clouds, accessing the personal data of millions of people worldwide. In 2021, data breach costs reached $4.35 million, hitting a record high, and are continually increasing. With preexisting encryption technologies, data cannot be searched without decrypting it first, which puts it at a higher risk of being accessed by malicious parties. Fully homomorphic encryption schemes solve this issue by eliminating the need to decrypt data to search it, and currently, there are no practical FHE schemes. According to market analysis, the fully homomorphic encryption market expects to grow at a rate of 7.50% from 2021 to 2028 to reach 437.30 million USD. A Clemson University researcher has developed a fully homomorphic encryption (FHE) method that allows data to be searched while remaining encrypted, reducing the risk of access for unauthorized parties.
As distributed computing becomes increasingly popular, there is an urgent need to protect the privacy of massive sensitive data stored in clouds and blockchains. The traditional encryption schemes can only allow searching on encrypted data with decryption first. The proposed fully homomorphic encryption method is a practical encryption scheme that protects the privacy of massive amounts of sensitive data stored in clouds, blockchains, and company databases. In addition, the FHE scheme allows for all possible searches to be performed in encrypted form and decrypted only by the data owner.
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