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Authors: Djedjiga Belhadj ; Yolande Belaïd and Abdel Belaïd

Affiliation: Université de Lorraine-LORIA,Campus Scientifique, 54500 Vandoeuvre-Lès-Nancy, France

Keyword(s): Information Extraction, Homomorphic Encryption, Polynomial Approximation, Attention Mechanism.

Abstract: This paper presents a homomorphic encryption (HE) system to extract information from business documents. We propose a structured method to replace the nonlinear activation functions of a multi-layer graph attention network (Multi-GAT), including ReLU, LeakyReLU, and the attention mechanism Softmax, with polynomials of different degrees. We also replace the normalization layers with an adapted HE algorithm. To solve the problem of accuracy loss during the approximation, we use a partially HE baseline model to train a fully HE model using techniques such as distillation knowledge and model fine-tuning. The proposed HE-friendly Multi-GAT models the document as a graph of words and uses the multi-head attention mechanism to classify the graph nodes. The first partially HE-Multi-GAT contains polynomial approximations of all ReLU, LeakyReLU and the attention Softmax activation functions. Normalization layers are used to handle values exploding when approximating all the nonlinear activatio n functions. These layers are approximated as well using an adapted algorithm that doesn’t rely on the training data and minimizes performances loss while avoiding connections between the server and the data owner. Experiments show that our approach minimizes the model accuracy loss. We tested the architecture on three different datasets and obtained competitive results (F1-scores greater than 93%). (More)

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Paper citation in several formats:
Belhadj, D.; Belaïd, Y. and Belaïd, A. (2024). Homomorphic Encryption Friendly Multi-GAT for Information Extraction in Business Documents. In Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-684-2; ISSN 2184-4313, SciTePress, pages 817-825. DOI: 10.5220/0012432400003654

@conference{icpram24,
author={Djedjiga Belhadj. and Yolande Belaïd. and Abdel Belaïd.},
title={Homomorphic Encryption Friendly Multi-GAT for Information Extraction in Business Documents},
booktitle={Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2024},
pages={817-825},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012432400003654},
isbn={978-989-758-684-2},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Homomorphic Encryption Friendly Multi-GAT for Information Extraction in Business Documents
SN - 978-989-758-684-2
IS - 2184-4313
AU - Belhadj, D.
AU - Belaïd, Y.
AU - Belaïd, A.
PY - 2024
SP - 817
EP - 825
DO - 10.5220/0012432400003654
PB - SciTePress

- Science and Technology Publications, Lda.
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