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GENIE watermarking scheme protects GNNs for link prediction

By PulseAugur Editorial · [1 sources] ·

Researchers have developed GENIE, a novel watermarking scheme designed to protect Graph Neural Network (GNN) models used for link prediction. Unlike previous methods that focused on node or graph classification, GENIE addresses the specific challenge of securing GNNs in link prediction tasks. The system employs a unique trigger set and a secret watermark vector, incorporating Dynamic Watermark Thresholding (DWT) to ensure high verification accuracy and robustness against various removal techniques and attacks. AI

IMPACT Provides a new method for protecting intellectual property in graph-based machine learning models.

RANK_REASON The cluster contains an academic paper detailing a new method for watermarking GNNs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

GENIE watermarking scheme protects GNNs for link prediction

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The cluster contains an academic paper detailing a new method for watermarking GNNs. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Venkata Sai Pranav Bachina, Aaryan Ajay Sharma, Ankit Gangwal, Charu Sharma ·

    GENIE: Watermarking Graph Neural Networks for Link Prediction

    arXiv:2406.04805v4 Announce Type: replace-cross Abstract: The rapid adoption, usefulness, and resource-intensive training of Graph Neural Network (GNN) models have made them an invaluable intellectual property in graph-based machine learning. However, their wide-spread adoption a…

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