| Title |
A unified classification model for quantum-enabled cyberattacks |
| Authors |
Krušniauskas, Simas ; Grigaliūnas, Šarūnas ; Brūzgienė, Rasa |
| Full Text |
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| Is Part of |
CEUR workshop proceedings: IVUS 2026: proceedings of the 31st international conference on information society and university studies (IVUS 2026), Kaunas, Lithuania, May 12, 2026 / edited by Audrius Lopata,Tomas Krilavičius, Ilona Veitaitė.. Aachen : CEUR-WS. 2026, vol. 4317, p. 1-10.. ISSN 1613-0073 |
| Keywords [eng] |
Quantum cybersecurity ; Post-Quantum cryptography ; Threat classification ; Crypto-agility |
| Abstract [eng] |
The rapid development of quantum computing is reshaping the cybersecurity threat landscape by undermining classical cryptographic assumptions and introducing new technical, operational, and organizational vulnerabilities. Existing cybersecurity threat frameworks insufficiently address quantumenabled risks, particularly those related to post-quantum cryptography (PQC) migration, hybrid infrastructures, and long-horizon threats such as store-now-decrypt-later attacks. This paper aims to develop a unified classification model for quantum-enabled cyberattacks that integrates cryptanalytic, protocol-level, operational, and human-factor dimensions into a structured analytical framework. The proposed model formalizes attack characterization through multidimensional parameters including attack vector, required quantum capability, exploited weakness, impact level, and temporal horizon, enabling systematic risk assessment. Experimental evaluation using simulated network traffic datasets demonstrated the model’s applicability for threat classification, risk scoring, and prioritization of PQC migration efforts. Results indicate that cryptanalytic and data-harvesting attacks present the highest long-term risk, while operational and human-factor vulnerabilities remain critical in the near term, highlighting the need for a comprehensive, multilayered approach to quantum cybersecurity readiness. |
| Published |
Aachen : CEUR-WS |
| Type |
Conference paper |
| Language |
English |
| Publication date |
2026 |
| CC license |
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