arXiv：cs.AI· Henrik Nolte, Miriam Rateike, Mich\`ele Finck·· 5 小时前
欧盟 AI 法案中的鲁棒性与网络安全问题分析
Robustness and Cybersecurity in the EU Artificial Intelligence Act
AI 导读
该论文指出，欧盟 AI 法案（AIA）第 15 条（高风险 AI 系统）和第 55 条（通用 AI 模型）中关于鲁棒性与网络安全的规定存在法律挑战与不足，并强调鲁棒性与网络安全要求系统具备抵御性能中断的能力。研究结合近期机器学习文献，评估了这些条款的实施难点，旨在为 Art. 15(2) AIA 下的协调标准、欧盟委员会指南及基准测试与测量方法提供参考，弥合法律术语与 ML 研究之间的差距。
正文
Abstract:The EU Artificial Intelligence Act (AIA) establishes different legal principles for different types of AI systems. While prior work has sought to clarify some of these principles, little attention has been paid to robustness and cybersecurity. This paper aims to fill this gap. We identify legal challenges and shortcomings in provisions related to robustness and cybersecurity for high-risk AI systems(Art. 15 AIA) and general-purpose AI models (Art. 55 AIA). We show that robustness and cybersecurity demand resilience against performance disruptions. Furthermore, we assess potential challenges in implementing these provisions in light of recent advancements in the machine learning (ML) literature. Our analysis informs efforts to develop harmonized standards, guidelines by the European Commission, as well as benchmarks and measurement methodologies under Art. 15(2) AIA. With this, we seek to bridge the gap between legal terminology and ML research, fostering a better alignment between research and implementation efforts.
| Comments: | A previous version contained an incorrect publication year for the AI Act on page 1. This has been corrected |
| Subjects: | Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR); Computers and Society (cs.CY); Machine Learning (cs.LG) |
| Cite as: | arXiv:2502.16184 [cs.AI] |
| (or arXiv:2502.16184v4 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2502.16184 arXiv-issued DOI via DataCite |
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| Journal reference: | The 2025 ACM Conference on Fairness, Accountability, and Transparency |
| Related DOI: | https://doi.org/10.1145/3715275.3732020
DOI(s) linking to related resources |
Submission history
From: Miriam Rateike [view email]
[v1]
Sat, 22 Feb 2025 11:12:20 UTC (598 KB)
[v2]
Wed, 28 May 2025 12:48:43 UTC (588 KB)
[v3]
Sat, 25 Jul 2026 09:59:53 UTC (601 KB)
[v4]
Sat, 10 Oct 2026 15:26:35 UTC (601 KB)
来源：arXiv：cs.AI · arxiv.org