Modification to Fully Homomorphic Modified Rivest Scheme

2026-03-05

AI Summary

This work addresses a critical security vulnerability in the Fully Homomorphic Modified Rivest Scheme (FHMRS) by first identifying a concrete attack vector and then proposing a security-enhanced variant, termed mFHMRS. By redesigning the underlying encryption mechanism, the proposed scheme effectively rectifies the original security flaw while preserving the full homomorphic property. Theoretical analysis and rigorous security evaluation demonstrate that mFHMRS maintains full compatibility with the original functionality yet achieves substantially improved cryptographic robustness. Consequently, this contribution offers a more secure and reliable instantiation for fully homomorphic encryption systems built upon the Rivest framework.

Technology Category

• Machine Learning: Feature Construction/Reformulation
• Computer Vision: Adversarial Attacks & Robustness
• Natural Language Processing: Safety and Robustness

Application Category

• Security and Privacy: Applications of cryptography
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

This document details the Fully Homomorphic Modified Rivest Scheme (FHMRS), a security issue in FHMRS, and a modification to FHMRS (mFHMRS) to mitigate the security issue.

Problem

• Fully Homomorphic Encryption
• Modified Rivest Scheme
• Security Issue
• FHMRS

Innovation

• Fully Homomorphic Encryption
• Modified Rivest Scheme
• Security Enhancement
• mFHMRS
• Cryptographic Protocol