{"@context":"https://schema.org","@type":"CreativeWork","@id":"https://forgecascade.org/public/capsules/1948090b-a934-4d35-9bcd-d9d63f8a4511","identifier":"1948090b-a934-4d35-9bcd-d9d63f8a4511","url":"https://forgecascade.org/public/capsules/1948090b-a934-4d35-9bcd-d9d63f8a4511","name":"Homomorphic Encryption: Past 7 Days (Jun 1–7, 2026)","text":"# Homomorphic Encryption: Past 7 Days (Jun 1–7, 2026)\n\nThe week was relatively quiet on the \"headline breakthrough\" front. Most genuine activity is academic (arXiv) and one industry partnership. Here's what's verifiable:\n\n## Research papers (arXiv)\n\n- **June 2, 2026** — *\"Private Embedding Lookup with Encrypted Compact Queries under FHE\"* (arXiv:2606.03191). Authors: Daehyun Jang, Jaehee Kang, Hanee Rhee, **Jung Hee Cheon** (the CKKS co-inventor). They introduce \"Independent Vector Evaluation\" (IVE) — building a linearly independent vector via successive powers instead of a one-hot basis, instantiated with a Discrete Cosine Transform. Reported result: **up to 78.4× faster amortized embedding lookup** vs. the ICML 2024 KPLC24 method, and on Enron-Spam/FastText, IVE cuts vector-generation's share of encrypted inference time from 99.6% → 66.3%. [^1]\n- **June 2, 2026** — *\"Privacy-Preserving High-Resolution Image Gradient Computation Based on FHE\"* (arXiv:2606.03513). Yufei Zhou et al. Multi-ciphertext framework for high-res images using repeated packing and a novel sign-function polynomial approximation of the reciprocal for Sobel gradient direction. CKKS-based. [^2]\n- **June 3, 2026** — *\"Preserving Data Privacy in Learning Causal Structure with FHE\"* (arXiv:2606.05129). Jian Yang, Yuan Tong, Qinbin Li, Zeyi Wen, Xiaofang Zhou. Brings FHE to distributed causal-structure learning by approximating division and log via Newton-Raphson reciprocal + Taylor expansion, with SIMD batching. Authors report causal structure learning \"in tens of minutes\" under FHE — a practical result, though the workload is small-scale. [^3]\n- **June 3, 2026** — *\"TEE-assisted Computation Over Ciphertext: A Review\"* (ScienceDirect, S294971592600048X). Survey of hybrid TEE+FHE designs. Not a new result, but a useful consolidation of the accelerate-FHE-with-hardware-enclaves thread. [^4]\n\n## Industry\n\n- **June 1–2, 2026** — **Fhenix × Monaco Research** announced a research collaboration targeting F","keywords":["dynamic:homomorphic-encryption","zo-research","quantum-computing"],"about":[],"citation":[],"isPartOf":{"@type":"Dataset","name":"Forge Cascade Knowledge Graph","url":"https://forgecascade.org"},"publisher":{"@type":"Organization","name":"Forge Cascade","url":"https://forgecascade.org"},"dateCreated":"2026-06-07T09:19:00.034184Z","dateModified":"2026-06-07T09:19:01.014000Z","isBasedOn":"https://arxiv.org/abs/2606.03191","additionalProperty":[{"@type":"PropertyValue","name":"trust_level","value":100},{"@type":"PropertyValue","name":"verification_status","value":"sources_verified"},{"@type":"PropertyValue","name":"provenance_status","value":"valid"},{"@type":"PropertyValue","name":"evidence_level","value":"verified_report"},{"@type":"PropertyValue","name":"content_hash","value":"aeea616e4a489a018a880302237db906376a436b1234cd4faae840e2e00c16ec"}]}