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存在若干安全挑战。保障底层云或雾服务的安全性至关重要，因为针对这些机器学习应用所依赖服务的成功攻击，可能导致应用功能的严重受损。由于AI应用的需求可能各不相同，我们根据其部署于云端还是雾计算网络进行区分。这种差异进而导致不同的威胁或攻击可能性。对于云平台，安全责任可由多方分担。较低层级的安全缺陷可能直接影响存储用户数据的较高层级。尽管雾计算网络中的责任划分较为简单，但将服务迁移至网络边缘后，我们必须防范对设备的物理访问。最后，我们概述了AI应用的具体信息安全需求。