HackerPapers

arXiv:2301.07041cs.CR

Verifiable Fully Homomorphic Encryption

Alexander Viand, Christian Knabenhans, Anwar Hithnawi

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

Fully Homomorphic Encryption (FHE) is seeing increasing real-world deployment to protect data in use by allowing computation over encrypted data. However, the same malleability that enables homomorphic computations also raises integrity issues, which have so far been mostly overlooked. While FHEs lack of integrity has obvious implications for correctness, it also has severe implications for confidentiality: a malicious server can leverage the lack of integrity to carry out interactive key-recovery attacks. As a result, virtually all FHE schemes and applications assume an honest-but-curious server who does not deviate from the protocol. In practice, however, this assumption is insufficient for a wide range of deployment scenarios. While there has been work that aims to address this gap, these have remained isolated efforts considering only aspects of the overall problem and fail to fully address the needs and characteristics of modern FHE schemes and applications. In this paper, we analyze existing FHE integrity approaches, present attacks that exploit gaps in prior work, and propose a new notion for maliciously-secure verifiable FHE. We then instantiate this new notion with a range of techniques, analyzing them and evaluating their performance in a range of different settings. We highlight their potential but also show where future work on tailored integrity solutions for FHE is still required.

arXiv comments
13 pages + References + Appendix
Journal reference
DOI
Subjects
cs.CRCryptography and Security

On Hacker News

Linked by 1 identifiable commenter in 1 comment across 1 thread, from Dec 2025 to Dec 2025.

Comments linking this paper, per year.

Discussed in comments1 thread

    • Building Arivu: CLI/library that normalizes fetch/search across a bunch of sources (arXiv, PubMed, HN, GitHub, Reddit, YouTube transcripts, RSS, web pages…). I use it as a context fetcher i.e grab an abstract/transcript/thread as clean text/JSON, pipe it into summaries or…

      TsarpView on HNParent context

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.