Size-Efficient Encryption Scheme that Secures Clouds and Blockchains

Market Overview:

This encryption method provides the ability for users of cloud storage platforms to retrieve or query encrypted information or data without having to first 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 2017, data breaches jumped to 29 percent in the United States alone; hitting a record high. With preexisting encryption technologies, data cannot be searched without decrypting it first, which puts it at a higher risk of being accessed to malicious parties. A Clemson University researcher has developed an fully homomorphic encryption (FHE) method that allows data to be searched while still remaining encrypted, reducing the risk of access for unauthorized parties.


Application                                                                   Stage of Development

Encryption, Data Security                                               Prototype



  • Data is encrypted with a private key, decrypting only for the user with the private key
  • Data encryption has a much smaller cipher-text expansion, reducing the total file size
  • All search functions can be performed with this method, allowing information to be found in encrypted form


Technical Summary

As distributed computing becomes more and more popular, there is an urgent need to protect privacy of massive sensitive data stored in clouds and blockchains. The traditional encryption schemes can not allow searching on encrypted data without 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 to this, the FHE scheme allows for all possible searches to be performed in encrypted form, and decrypted by the data owner.

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Inventor:                       Shuhong Gao

Patent Type:                  Provisional 

Serial Number:             62/687,681

CURF Ref No:              2018-004

Patent Information:
For Information, Contact:
Mark Roth
Business Development Associate
Clemson University Research Foundation
Shuhong Gao
Computer Software
Cyber-Security/Security Systems
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