Homomorphic encryption allows computations to be performed on encrypted data without decrypting it, providing strong privacy guarantees. However, the adoption of homomorphic encryption is challenging due to several factors:
A . Incomplete mathematical primitives: This is not the primary barrier as the theoretical foundations of homomorphic encryption are well-developed.
B . No use cases to drive adoption: There are several compelling use cases for homomorphic encryption, especially in privacy-sensitive fields like healthcare and finance.
C . Quantum computers not yet capable: Quantum computing is not directly related to the challenges of adopting homomorphic encryption.
D . Insufficient coprocessor support: The computational overhead of homomorphic encryption is significant, requiring substantial processing power. Current general-purpose processors are not optimized for the intensive computations required by homomorphic encryption, limiting its practical deployment. Specialized hardware or coprocessors designed to handle these computations more efficiently are not yet widely available.
Reference:
CompTIA Security+ Study Guide
"Homomorphic Encryption: Applications and Challenges" by Rivest et al.
NIST, "Report on Post-Quantum Cryptography"