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English(EN) A Comprehensive Review of One-Pixel Attack: Research Status, Taxonomy, Applications, Regulation Policy and Future Directions

综述论文详述一像素攻击并提出人工智能安全监管

一篇新发表在arXiv上的综述论文详细介绍了“一像素攻击”(One-Pixel Attacks, OPAs)的研究现状。OPA是一种深度学习中的对抗性攻击,通过修改单个像素即可导致模型误分类。该论文综合了2017年至2026年的研究,提供了OPA研究的分类,包括算法基础、防御机制和特定领域的漏洞。论文强调了基于差分进化策略的普遍性,并指出了数据集多样性和评估标准方面存在的持续性差距。该综述还提出了一个人工智能安全治理的监管框架。 AI

影响 强调了人工智能系统的漏洞并提出了人工智能安全监管框架。

排序理由 该条目是一篇发表在arXiv上的综合性综述论文。[lever_c_demoted from research: ic=1 ai=1.0]

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综述论文详述一像素攻击并提出人工智能安全监管

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该条目是一篇发表在arXiv上的综合性综述论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Mirza Niaz Morshed, Md. Masudul Islam, Galib Muhammad Shahriar Himel, Md. Aslam Uddin, Hui Liu, Md. Shafiqul Islam ·

    一像素攻击的全面综述:研究现状、分类、应用、监管政策及未来方向

    arXiv:2610.00125v1 Announce Type: cross Abstract: One-Pixel Attacks (OPAs) represent one of the most extreme demonstrations of adversarial fragility in deep learning, where modifying a single pixel can reliably induce high-confidence misclassification across domains such as medic…