GKS fully homomorphic encryption enables secure computing on data
GKS Fully Homomorphic Encryption: Security Analysis
Cryptography and Security
Summary
Normally, encrypted information must be unlocked before it can be used, which risks exposing it. The authors analyze a special encryption method called GKS that lets computers work with encrypted data directly without needing to unlock it first. This method avoids complicated steps needed by other systems, produces exact outputs, supports searching within encrypted data, and can handle unlimited computations. Their work shows how secure this method is, helping make private data operations safer.
What this means in practice
- •For cloud service providers: Offer secure computing on encrypted customer data without costly operations or output inaccuracy using GKS encryption.$Commercial implications: Enables cloud vendors to sell privacy-preserving processing services with exact outputs and no bootstrapping overhead.
- •For enterprise security teams: Implement encrypted search over sensitive corporate data without decrypting it, enhancing data privacy and compliance.
Authors
John Graham, Soundes Marzougui, Miloš Pavlović, Vladimir Shpilrain
Abstract
All traditional encryption schemes share a fundamental operational vulnerability: encrypted data must be decrypted before it can be used. Fully homomorphic encryption eliminates this vulnerability by enabling computation directly on encrypted data, but existing FHE schemes impose substantial practical constraints that limit deployment. This paper presents a formal security analysis of the Gribov-Kahrobaei-Shpilrain (GKS) private-key FHE scheme. GKS requires no bootstrapping or de-linearization, produces bit-exact decryption, supports native encrypted search, and scales to unbounded depth.