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Adaptive quantum-walk-inspired attack graph compiler for vulnerability-aware exploration and explainable cybersecurity attack path prioritization PRIMARY_TEXT

Scientific Reports · 2026-09-09 · no page hash: the reader saw a rendering, not the bytes · created seq 20379

Link: https://www.nature.com/articles/s41598-026-69771-1 · read at 2026-09-29T01:50:54Z · held by reference: only the link, the quoted excerpts with their hashes, and the page hash when the reader had the bytes are stored

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This paper proposes the Adaptive Quantum-Walk-Inspired Attack Graph Compiler (AQAGC), a hybrid quantum–classical attack graph analytics framework that employ...normalized — the passage is on the page once typography is folded together
A derived multi-scale attack graph benchmark was constructed from the CIC-IDS2017, UNSW-NB15, CSE-CIC-IDS2018, and ToN-IoT datasets, comprising standardized ...normalized — the passage is on the page once typography is folded together
Experimental results demonstrate that AQAGC consistently outperforms classical graph-search, probabilistic, quantum-walk-based, and hybrid quantum baselines ...verbatim — the passage is on the page, character for character

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QUOTE {}This paper proposes the Adaptive Quantum-Walk-Inspired Attack Graph Compiler (AQAGC), a hybrid quantum–classical attack graph analytics framework that employs quantum walk principles to improve attack-path discovery, prioritization, and ...
QUOTE {}A derived multi-scale attack graph benchmark was constructed from the CIC-IDS2017, UNSW-NB15, CSE-CIC-IDS2018, and ToN-IoT datasets, comprising standardized attack graphs containing 50 to 5000 nodes.
QUOTE {}Experimental results demonstrate that AQAGC consistently outperforms classical graph-search, probabilistic, quantum-walk-based, and hybrid quantum baselines in attack-path discovery, ranking quality, scalability, robustness, and explaina...

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