A financial services company wants to analyze sensitive customer data on a third-party cloud platform without exposing the raw data to the cloud provider. A security architect proposes using fully homomorphic encryption (FHE). While this solution meets the privacy goal of processing encrypted data, the implementation team is hesitant. Which of the following represents the most significant barrier to implementing this FHE-based solution for large-scale data analytics?
The correct answer is Significantly greater computational requirements. The most significant challenge and primary barrier to the widespread adoption of homomorphic encryption is its extremely high computational overhead and performance impact. Operations performed on data encrypted with homomorphic schemes are thousands to millions of times slower than the same operations on plaintext data, which can make it impractical for real-time or large-scale analytics applications.
Vulnerability to quantum computing attacks is incorrect. Many modern fully homomorphic encryption schemes are built on lattice-based cryptography, which is currently considered to be resistant to attacks from quantum computers.
Incompatibility with existing PKI systems is incorrect. Homomorphic encryption is a type of asymmetric (public-key) cryptography and is therefore conceptually compatible with Public Key Infrastructure (PKI) for managing its public and private keys.
Higher risk of side-channel attacks is incorrect. While homomorphic encryption implementations can be vulnerable to side-channel attacks like other cryptographic systems, this is not considered its primary or most significant drawback compared to the massive performance overhead.
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ISC2 CISSP
Security Architecture and Engineering
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