This article deals with the IT security of connectionist artificial intelligence (AI) applications, focusing on threats to integrity, one of the three IT security goals. Such threats are for instance most relevant in prominent AI computer vision applications. In order to present a holistic view on the IT security goal integrity, many additional aspects such as interpretability, robustness and documentation are taken into account. A comprehensive list of threats and possible mitigations is presented by reviewing the state-of-the-art literature. AI-specific vulnerabilities such as adversarial attacks and poisoning attacks as well as their AI-specific root causes are discussed in detail. Additionally and in contrast to former reviews, the whole AI supply chain is analysed with respect to vulnerabilities, including the planning, data acquisition, training, evaluation and operation phases. The discussion of mitigations is likewise not restricted to the level of the AI system itself but rather advocates viewing AI systems in the context of their supply chains and their embeddings in larger IT infrastructures and hardware devices. Based on this and the observation that adaptive attackers may circumvent any single published AI-specific defence to date, the article concludes that single protective measures are not sufficient but rather multiple measures on different levels have to be combined to achieve a minimum level of IT security for AI applications.

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Connectionist AI 应用的漏洞：评估和防御

本文讨论连接主义人工智能 (AI) 应用程序的 IT 安全，重点关注完整性威胁，这是三个 IT 安全目标之一。例如，此类威胁与突出的 AI 计算机视觉应用最为相关。为了提供有关 IT 安全目标完整性的整体视图，还考虑了许多其他方面，例如可解释性、稳健性和文档。通过查看最先进的文献，提供了威胁和可能的缓解措施的完整列表。详细讨论了 AI 特定的漏洞，例如对抗性攻击和中毒攻击，以及它们特定于 AI 的根本原因。此外，与之前的审查相比，整个 AI 供应链都针对漏洞进行了分析，包括计划、数据获取、培训、评估和操作阶段。对缓解措施的讨论同样不限于 AI 系统本身的级别，而是提倡在其供应链及其嵌入大型 IT 基础设施和硬件设备的背景下查看 AI 系统。基于这一点以及自适应攻击者可能绕过迄今为止任何单一发布的特定于人工智能的防御的观察，本文得出结论，单一的保护措施是不够的，必须将不同级别的多种措施结合起来才能实现最低级别的 IT 安全。用于人工智能应用。对缓解措施的讨论同样不限于 AI 系统本身的级别，而是提倡在其供应链及其嵌入大型 IT 基础设施和硬件设备的背景下查看 AI 系统。基于这一点以及自适应攻击者可能绕过迄今为止任何单一发布的特定于人工智能的防御的观察，本文得出结论，单一的保护措施是不够的，必须将不同级别的多种措施结合起来才能实现最低级别的 IT 安全。用于人工智能应用。对缓解措施的讨论同样不限于 AI 系统本身的级别，而是提倡在其供应链及其嵌入大型 IT 基础设施和硬件设备的背景下查看 AI 系统。基于这一点以及自适应攻击者可能绕过迄今为止任何单一发布的特定于人工智能的防御的观察，本文得出结论，单一的保护措施是不够的，必须将不同级别的多种措施结合起来才能实现最低级别的 IT 安全。用于人工智能应用。