Adversarial Limits of Quantum Certification: When Eve Defeats Detection

• URL: http://arxiv.org/abs/2512.04391v1
• Date: Thu, 04 Dec 2025 02:24:04 GMT
• Title: Adversarial Limits of Quantum Certification: When Eve Defeats Detection
• Authors: Davut Emre Tasar,
• Abstract summary: Security of quantum key distribution relies on certifying that observed correlations arise from genuine quantum entanglement.<n>Eve GAN is a generative adversarial network trained to produce classical correlations indistinguishable from quantum.<n>We find that same distribution calibration a common practice in prior certification studies inflates detection performance by 44 percentage points.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Security of quantum key distribution (QKD) relies on certifying that observed correlations arise from genuine quantum entanglement rather than eavesdropper manipulation. Theoretical security proofs assume idealized conditions, practical certification must contend with adaptive adversaries who optimize their attack strategies against detection systems. Established fundamental adversarial limits for quantum certification using Eve GAN, a generative adversarial network trained to produce classical correlations indistinguishable from quantum. Our central finding: when Eve interpolates her classical correlations with quantum data at mixing parameter, all tested detection methods achieve ROC AUC = 0.50, equivalent to random guessing. This means an eavesdropper needs only 5% classical admixture to completely evade detection. Critically, we discover that same distribution calibration a common practice in prior certification studies inflates detection performance by 44 percentage points compared to proper cross distribution evaluation, revealing a systematic flaw that may have led to overestimated security claims. Analysis of Popescu Rohrlich (PR Box) regime identifies a sharp phase transition at CHSH S = 2.05: below this value, no statistical method distinguishes classical from quantum correlations; above it, detection probability increases monotonically. Hardware validation on IBM Quantum demonstrates that Eve-GAN achieves CHSH = 2.736, remarkably exceeding real quantum hardware performance (CHSH = 2.691), illustrating that classical adversaries can outperform noisy quantum systems on standard certification metrics. These results have immediate implications for QKD security: adversaries maintaining 95% quantum fidelity evade all tested detection methods. We provide corrected methodology using cross-distribution calibration and recommend mandatory adversarial testing for quantum security claims.

Related papers

• Continual Quantum Architecture Search with Tensor-Train Encoding: Theory and Applications to Signal Processing [68.35481158940401]
  CL-QAS is a continual quantum architecture search framework.<n>It mitigates challenges of costly encoding amplitude and forgetting in variational quantum circuits.<n>It achieves controllable robustness expressivity, sample-efficient generalization, and smooth convergence without barren plateaus.
  arXiv  Detail & Related papers  (2026-01-10T02:36:03Z)
• TARA Test-by-Adaptive-Ranks for Quantum Anomaly Detection with Conformal Prediction Guarantees [0.0]
  Quantum key distribution (QKD) security relies on the ability to distinguish genuine quantum correlations from classical eavesdropper simulations.<n>We introduce TARA, a novel framework combining conformal prediction with sequential martingale testing for quantum anomaly detection.
  arXiv  Detail & Related papers  (2025-12-03T17:53:38Z)
• Formal Verification of Noisy Quantum Reinforcement Learning Policies [0.0]
  Quantum reinforcement learning (QRL) aims to use quantum effects to create sequential decision-making policies.<n> QRL policies face uncertainty from quantum measurements and hardware noise, such as bit-flip, phase-flip, and depolarizing errors.<n>We introduce QVerifier, a formal verification method that applies probabilistic model checking to analyze trained QRL policies.
  arXiv  Detail & Related papers  (2025-12-01T10:26:33Z)
• QMA Complete Quantum-Enhanced Kyber: Provable Security Through CHSH Nonlocality [1.5469452301122173]
  Post-quantum cryptography must secure large-scale communication systems against quantum adversaries.<n>We introduce the first Clauser-e-Shimony-Holt (CHSH)-certified Kyber protocol, which embeds quantum non-locality verification directly within the key exchange phase.<n>The resulting CHSH-augmented Kyber scheme establishes a mathematically rigorous, hybrid post-quantum framework.
  arXiv  Detail & Related papers  (2025-11-15T18:31:36Z)
• Quantum Gated Recurrent GAN with Gaussian Uncertainty for Network Anomaly Detection [10.435718832887988]
  Anomaly detection in time-series data is a critical challenge with significant implications for network security.<n>Recent quantum machine learning approaches have shown promise in capturing complex data distributions for anomaly detection but remain constrained by limited qubit counts.<n>We introduce in this work a novel Quantum Gated Recurrent Unit (QGRU)-based Generative Adversarial Network (GAN) for robust network anomaly detection.
  arXiv  Detail & Related papers  (2025-10-30T13:39:44Z)
• Bayesian Quantum Amplitude Estimation [46.03321798937855]
  We present BAE, a problem-tailored and noise-aware Bayesian algorithm for quantum amplitude estimation.<n>In a fault tolerant scenario, BAE is capable of saturating the Heisenberg limit; if device noise is present, BAE can dynamically characterize it and self-adapt.<n>We propose a benchmark for amplitude estimation algorithms and use it to test BAE against other approaches.
  arXiv  Detail & Related papers  (2024-12-05T18:09:41Z)
• QuanTest: Entanglement-Guided Testing of Quantum Neural Network Systems [45.18451374144537]
  Quantum Neural Network (QNN) combines the Deep Learning (DL) principle with the fundamental theory of quantum mechanics to achieve machine learning tasks with quantum acceleration. QNN systems differ significantly from traditional quantum software and classical DL systems, posing critical challenges for QNN testing. We propose QuanTest, a quantum entanglement-guided adversarial testing framework to uncover potential erroneous behaviors in QNN systems.
  arXiv  Detail & Related papers  (2024-02-20T12:11:28Z)
• Classical certification of quantum gates under the dimension assumption [0.1874930567916036]
  We introduce a certification method for quantum gates tailored for a practical server-user scenario.<n>For single-qubit gates, including those that form a universal set for single-qubit quantum computation, we demonstrate that our approach offers soundness guarantees.
  arXiv  Detail & Related papers  (2024-01-30T13:40:39Z)
• Hierarchical certification of nonclassical network correlations [50.32788626697182]
  We derive linear and nonlinear Bell-like inequalities for networks, whose violation certifies the absence of a minimum number of classical sources in them. We insert this assumption, which leads to results more amenable to certification in experiments.
  arXiv  Detail & Related papers  (2023-06-27T18:00:01Z)
• Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine Learning [47.991114317813555]
  Quantum models implement implicit probabilistic predictors that produce multiple random decisions for each input through measurement shots. This paper proposes to leverage such randomness to define prediction sets for both classification and regression that provably capture the uncertainty of the model.
  arXiv  Detail & Related papers  (2023-04-06T22:05:21Z)
• Simple Tests of Quantumness Also Certify Qubits [69.96668065491183]
  A test of quantumness is a protocol that allows a classical verifier to certify (only) that a prover is not classical. We show that tests of quantumness that follow a certain template, which captures recent proposals such as (Kalai et al., 2022) can in fact do much more. Namely, the same protocols can be used for certifying a qubit, a building-block that stands at the heart of applications such as certifiable randomness and classical delegation of quantum computation.
  arXiv  Detail & Related papers  (2023-03-02T14:18:17Z)
• Certified Robustness of Quantum Classifiers against Adversarial Examples through Quantum Noise [68.1992787416233]
  We show that adding quantum random rotation noise can improve robustness in quantum classifiers against adversarial attacks. We derive a certified robustness bound to enable quantum classifiers to defend against adversarial examples.
  arXiv  Detail & Related papers  (2022-11-02T05:17:04Z)
• Efficient and robust certification of genuine multipartite entanglement in noisy quantum error correction circuits [58.720142291102135]
  We introduce a conditional witnessing technique to certify genuine multipartite entanglement (GME) We prove that the detection of entanglement in a linear number of bipartitions by a number of measurements scales linearly, suffices to certify GME. We apply our method to the noisy readout of stabilizer operators of the distance-three topological color code and its flag-based fault-tolerant version.
  arXiv  Detail & Related papers  (2020-10-06T18:00:07Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.