LETIndex: A Secure Learned Index with TEE
Summary: LETIndex: a learned index for TEE-protected databases that organizes PGM models in an LSM layout and uses adaptive prefetch to cut enclave transitions and disk I/O. Enables lookups, range queries, and updates with far fewer context switches than REE-buffer/parameter-tuning baselines; outperforms on SOSD and improves join workloads. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Shuting Cao
- 2. Zeping Niu
- 3. Guoliang Li
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 101 | The Case for Learned Index Structures | 2018 | SIGMOD | 0.00049778866 |
| 844 | The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds | 2020 | VLDB | 0.00015964123 |
| 1,438 | Benchmarking Learned Indexes | 2021 | VLDB | 0.00011965956 |
| 3,882 | Building Enclave-Native Storage Engines for Practical Encrypted Databases | 2021 | VLDB | 6.6636559e-05 |
| 5,072 | Learned Index: A Comprehensive Experimental Evaluation | 2023 | VLDB | 5.7121108e-05 |
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