Berghoff Christian, Neu Matthias, von Twickel Arndt
Federal Office for Information Security, Bonn, Germany.
Front Big Data. 2020 Jul 22;3:23. doi: 10.3389/fdata.2020.00023. eCollection 2020.
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 are discussed in detail, together with key factors underlying them. Additionally and in contrast to former reviews, the whole AI life cycle is analyzed 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 life cycles 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 defense 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.
本文探讨联结主义人工智能（AI）应用的信息技术安全，重点关注对完整性的威胁，完整性是信息技术安全的三个目标之一。此类威胁在著名的人工智能计算机视觉应用中最为相关。为了全面呈现信息技术安全目标中的完整性，还考虑了许多其他方面，如可解释性、鲁棒性和文档记录。通过回顾最新文献，列出了一份全面的威胁及可能的缓解措施清单。详细讨论了人工智能特有的漏洞，如对抗攻击和中毒攻击，以及其背后的关键因素。此外，与以往的综述不同，本文还针对漏洞分析了人工智能的整个生命周期，包括规划、数据采集、训练、评估和运营阶段。缓解措施的讨论同样不限于人工智能系统本身的层面，而是主张在人工智能系统的生命周期以及它们在更大的信息技术基础设施和硬件设备中的嵌入背景下看待人工智能系统。基于此以及观察到自适应攻击者可能会规避迄今为止任何已发布的特定于人工智能的防御措施，本文得出结论，单一的保护措施是不够的，必须在不同层面上结合多种措施，以实现人工智能应用的最低信息技术安全水平。
