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New Q-DIBA attack targets quantum neural networks with dynamic triggers

By PulseAugur Editorial · [4 sources] ·

Researchers have developed Q-DIBA, the first input-aware dynamic backdoor attack specifically designed for Quantum Neural Networks (QNNs). This novel attack generates a unique trigger for each input, overcoming limitations of previous fixed-trigger attacks that were more easily detected. Q-DIBA demonstrates effectiveness and stealthiness in experiments on MNIST and Fashion-MNIST datasets, proving resilient against common defenses and highlighting a significant security threat for QNN deployment. AI

IMPACT Highlights a new security vulnerability in quantum neural networks, potentially impacting their adoption and requiring new defense mechanisms.

RANK_REASON The cluster describes a new academic paper detailing a novel attack method against quantum neural networks.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 4 sources. How we write summaries →

New Q-DIBA attack targets quantum neural networks with dynamic triggers

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The cluster describes a new academic paper detailing a novel attack method against quantum neural networks.
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COVERAGE [4]

  1. arXiv cs.LG TIER_1 English(EN) · Junrui Zhang, Zemin Chen, Lusi Li, Mohammad Ghasemigol, Daniel Takabi, Rui Ning ·

    Input-Aware Dynamic Backdoor Attack Against Quantum Neural Networks

    arXiv:2607.11843v1 Announce Type: cross Abstract: Quantum Neural Networks (QNNs) are a promising framework for quantum machine learning on near-term quantum devices, but their security risks remain insufficiently understood. Studies have shown that QNNs are vulnerable to backdoor…

  2. arXiv cs.LG TIER_1 English(EN) · Rui Ning ·

    Input-Aware Dynamic Backdoor Attack Against Quantum Neural Networks

    Quantum Neural Networks (QNNs) are a promising framework for quantum machine learning on near-term quantum devices, but their security risks remain insufficiently understood. Studies have shown that QNNs are vulnerable to backdoor attacks, yet existing quantum backdoors mostly re…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    Input-Aware Dynamic Backdoor Attack Against Quantum Neural Networks

    Quantum Neural Networks (QNNs) are a promising framework for quantum machine learning on near-term quantum devices, but their security risks remain insufficiently understood. Studies have shown that QNNs are vulnerable to backdoor attacks, yet existing quantum backdoors mostly re…

  4. Mastodon — mastodon.social TIER_1 English(EN) · notatechguy ·

    Quantum neural network backdoor attack adapts per input Researchers propose Q-DIBA, a backdoor attack generating a unique trigger for each input to quantum neur

    Quantum neural network backdoor attack adapts per input Researchers propose Q-DIBA, a backdoor attack generating a unique trigger for each input to quantum neural networks, evading three tested defenses. https://www. notatechguy.com/quantum-neural -network-backdoor-attack-adapts-…

    LINKS notatechguy.com/quantum-neural-network-ba…

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