On the Sensitivity to Errors in Homomorphic Computing: Single Transient Bit-flip Client-side Error Characterization
Homomorphic Encryption (HE) enables computation on encrypted data without decryption and is a key primitive for privacy-preserving computation in sensitive domains such as healthcare, finance, and government. Its security relies on noise injection, which introduces intrinsic error sensitivity and raises concerns about the fault tolerance of HE systems, as hardware- and software-induced faults can evade traditional detection mechanisms and lead to silent data corruption. In this work, we analyze
Record details
Published: 11 August 2026
Source: arXiv cs.CR (AI security)
Category: Research
Topics: Privacy · Healthcare
Retrieved: 12 August 2026
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ethics.ai (11 August 2026), “On the Sensitivity to Errors in Homomorphic Computing: Single Transient Bit-flip Client-side Error Characterization,” evidence record 18678, https://ethics.ai/record/18678 (originally published by arXiv cs.CR (AI security)).
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