arXiv:2412.18442cs.CRcs.AI2024-12中稿 · the 3rd IEEE Confe…被引 15

系统梳理AI的攻击潜力,揭示其对人与系统的多重威胁

SoK: On the Offensive Potential of AI

  • 构建统一评估框架,整合学术、工业与公众视角
  • 分析95篇论文、38场安全会议及549人调研,发现多类隐蔽攻击方式
  • 为安全研究者提供对抗性AI威胁的全面参考

社会日益受益于人工智能,但越来越多证据表明,AI也被用于进攻性目的。已有研究揭示了多种部署AI可能违反安全与隐私目标的应用场景,但尚无工作能全面呈现进攻性AI的潜在能力。本文通过系统化知识整合(SoK),综合学术文献、工业会议(如BlackHat)、专家意见及549名不同背景用户的调查反馈,构建一套反映进攻性AI核心技术因素的通用评估标准。在此基础上,系统分析了95篇研究论文、38份信息安全简报、549人用户研究及12位专家观点,不仅揭示了当前被忽视的新型攻击路径,也为未来应对这一威胁奠定了基础。

原文摘要 · Abstract (English)

Our society increasingly benefits from Artificial Intelligence (AI). Unfortunately, more and more evidence shows that AI is also used for offensive purposes. Prior works have revealed various examples of use cases in which the deployment of AI can lead to violation of security and privacy objectives. No extant work, however, has been able to draw a holistic picture of the offensive potential of AI. In this SoK paper we seek to lay the ground for a systematic analysis of the heterogeneous capabilities of offensive AI. In particular we (i) account for AI risks to both humans and systems while (ii) consolidating and distilling knowledge from academic literature, expert opinions, industrial venues, as well as laypeople -- all of which being valuable sources of information on offensive AI. To enable alignment of such diverse sources of knowledge, we devise a common set of criteria reflecting essential technological factors related to offensive AI. With the help of such criteria, we systematically analyze: 95 research papers; 38 InfoSec briefings (from, e.g., BlackHat); the responses of a user study (N=549) entailing individuals with diverse backgrounds and expertise; and the opinion of 12 experts. Our contributions not only reveal concerning ways (some of which overlooked by prior work) in which AI can be offensively used today, but also represent a foothold to address this threat in the years to come.

AI安全攻击模型系统综述

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