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new research about Qubic selfish mining on Monero network
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_bibliography/papers.bib

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@INPROCEEDINGS{Qubic25,
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author={Suhyeon Lee, and Hyeongyeong Kim},
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booktitle={arXiv preprint arXiv:2505.24393},
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title={Inside Qubic's Selfish Mining Campaign on Monero: Evidence, Tactics, and Limits},
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year={2025},
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month={December},
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volume={},
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number={},
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pages={},
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keywords={blockchain, Proof-of-Work, selfish mining},
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abstract={We analyze Qubic's advertised selfish mining campaign on Monero in 2025. Combining data from Monero nodes, and the Qubic pool API, we reconstruct Qubic-attributed blocks and hashrate and detect ten intervals consistent with selfish mining strategies. In these intervals, Qubic's average hashrate share rises to the 23-34\% range, yet sustained 51\% control is never observed. We evaluate the campaign against the classical selfish mining model and a modified Markov-chain model that reflects Qubic's conservative release strategy: both predict lower revenue than honest mining at the inferred parameters, and the data largely confirms this while still showing noticeable deviations from the predicted curve. We interpret this gap between model and measurements in terms of Qubic's time-varying hashrate and coarse-grained attack segmentation.},
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html={https://arxiv.org/abs/2512.01437},
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pdf={https://arxiv.org/pdf/2512.01437},
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doi={https://doi.org/10.48550/arXiv.2512.01437},
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preview={2025Qubic.png},
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selected={true}
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}
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@INPROCEEDINGS{attention25,
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author={Suhyeon Lee},
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author={Suhyeon Lee, and Yeongju Bak},
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booktitle={arXiv preprint arXiv:2505.24393},
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title={Looking for Attention: Randomized Attention Test Design for Validator Monitoring in Optimistic Rollups},
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year={2025},
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