Security challenges for Cloud or Fog-based machine learning services pose several concerns. Securing the underlying Cloud or Fog services is essential, as successful attacks against these services, on which machine learning applications rely, can lead to significant impairments of these applications. Because the requirements for AI applications can also be different, we differentiate according to whether they are used in the Cloud or in a Fog Computing network. This then also results in different threats or attack possibilities. For Cloud platforms, the responsibility for security can be divided between different parties. Security deficiencies at a lower level can have a direct impact on the higher level where user data is stored. While responsibilities are simpler for Fog Computing networks, by moving services to the edge of the network, we have to secure them against physical access to the devices. We conclude by outlining specific information security requirements for AI applications.

翻译：基于云或雾计算的机器学习服务面临诸多安全挑战。保障底层云或雾服务的安全性至关重要，因为机器学习应用依赖这些服务，若针对这些服务的攻击得逞，将导致应用功能严重受损。由于人工智能应用的需求可能存在差异，我们根据其部署在云环境还是雾计算网络中进行分类讨论，进而得出不同威胁或攻击可能性。对于云平台，安全责任可由多方分担。底层安全缺陷可能直接影响存储用户数据的高层级。尽管雾计算网络的责任划分更为简单，但将服务迁移至网络边缘后，需防范设备遭受物理访问攻击。最后，我们概述了人工智能应用面临的特定信息安全需求。