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.

云端或雾计算的机器学习服务面临多个安全挑战，安全保障基础的云端或雾服务至关重要，攻击这些服务将对机器学习应用造成重大影响。根据应用于云端或雾计算网络的人工智能应用需求的不同，产生不同的威胁或攻击可能性，因此对安全需求也不同。本文通过将服务移到网络边缘的方式使得对雾计算网络的责任更简单，但需要确保它们不受物理设备访问的威胁。最后我们总结了人工智能应用的特定信息安全要求。