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A Review of Homomorphic Encryption Libraries for Secure Computation

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arxiv 1812.02428 v2 pith:BIS7ET63 submitted 2018-12-06 cs.CR

classification cs.CR
keywords encryptionhomomorphiclibrariescomputationfeaturessecureacrossapplications
verification ladder T0 review T1 audit T2 compute T3 formal
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In this paper we provide a survey of various libraries for homomorphic encryption. We describe key features and trade-offs that should be considered while choosing the right approach for secure computation. We then present a comparison of six commonly available Homomorphic Encryption libraries - SEAL, HElib, TFHE, Paillier, ELGamal and RSA across these identified features. Support for different languages and real-life applications are also elucidated.

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  1. Federated Learning: An approach with Hybrid Homomorphic Encryption

    cs.CR 2025-09 conditional novelty 6.0 of 10

    Pairing the PASTA stream cipher with BFV homomorphic encryption in federated learning cuts client upload by about 2000x and keeps MNIST accuracy within 1.3% of plaintext, but makes server aggregation roughly 15,000x m...

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