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Homomorphic encryption

Homomorphic encryption is a form of encryption that allows computation on ciphertexts, generating an encrypted result which, when decrypted, matches the result of the operations as if they had been performed on the plaintext.

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Industry

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Parent Industry
Encryption
Encryption
Cybersecurity
Cybersecurity

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Wikidata ID
Q2154943

Homomorphic encryption is cryptographic system that allows data to remain encrypted while it is in use. The system allows computations and data manipulations to be performed on a a cipher text, instead of the actual data itself, providing a more secure ecosystem for data interactions. The system allows encrypted data to remain encrypted while being manipulated without having to decrypt it first. It allows users to apply functions on the encrypted data without the values of the data being revealed.

Homomorphic encryption is based on an algebraic system, and uses arithmetic circuits instead of more commonly used Boolean circuits.

The use of partial homomorphic encryption systems has been used in cryptosystems designed for the financial, healthcare, and retail industries, cloud computing, and e-voting democratic election technologies. One such system is the Paillier cryptosystem, invented in 1999, which is an additive homomorphic encryption system.

History

Research on homomorphic encryption dates back to MIT researchers Ronald Rivest, Len Adleman and Michel Dertouzos. In 2009, Craig Gentry constructed the first fully homomorphic encryption scheme.

In 2016, two data security starts up, Duality Technologies and Enveil were founded with the goal of offering fully homomorphic encryption products that to consumers.

In December 2018, cryptographers at Microsoft Research released an open source homomorphic encryption library, Simple Encrypted Arithmetic Library (SEAL).

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Further Resources

Title
Author
Link
Type
Date

A Fully Homomorphic Encryption Scheme FULLY HOMOMORPHIC ENCRYPTION SCHEME

Craig Gentry

https://crypto.stanford.edu/craig/craig-thesis.pdf

Dissertation

2009

Analysis, Improvement and Simplification of Prêt à Voter with Paillier Encryption

Zhe Xia, Steve A. Schneider, James Heather

https://www.usenix.org/legacy/event/evt08/tech/full_papers/xia/xia_html/PAV-Paillier.html

Web

2008

Computing Arbitrary Functions of Encrypted Data

Craig Gentry

https://crypto.stanford.edu/craig/easy-fhe.pdf

Academic paper

2008

On Data Banks and Homomorphis Privacy

Ronald Rivest, Len Adelman, Michel Dertouzos

http://people.csail.mit.edu/rivest/RivestAdlemanDertouzos-OnDataBanksAndPrivacyHomomorphisms.pdf

Secure Search via Multi-Ring Fully Homomorphic Encryption

Adi Akavia, Dan Feldman, and Hayim Shaul

https://eprint.iacr.org/2018/245.pdf

Academic paper

References

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