in fifth-generation (5G) networks and beyond, communication latency and network bandwidth will be no longer be bottlenecks to mobile users. Thus, almost every mobile device can participate in distributed learning. That is, the availability issue of distributed learning can be eliminated. However, model safety will become a challenge. This is because the distributed learning system is prone to suffering from byzantine attacks during the stages of updating model parameters and aggregating gradients among multiple learning participants. Therefore, to provide the byzantine-resilience for distributed learning in the 5G era, this article proposes a secure computing framework based on the sharding technique of blockchain, namely PiRATE. To prove the feasibility of the proposed PiRATE, we implemented a prototype. A case study shows how the proposed PiRATE contributes to distributed learning. Finally, we also envision some open issues and challenges based on the proposed byzantine- resilient learning framework.

中文翻译：

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PiRATE：5G网络中基于区块链的分布式机器学习安全框架

在第五代（5G）及以后的网络中，通信延迟和网络带宽将不再成为移动用户的瓶颈。因此，几乎每个移动设备都可以参与分布式学习。即，可以消除分布式学习的可用性问题。但是，模型安全性将成为一个挑战。这是因为在更新模型参数和聚集多个学习参与者之间的梯度的阶段中，分布式学习系统易于遭受拜占庭式攻击。因此，为在5G时代为分布式学习提供拜占庭式弹性，本文提出了一种基于区块链分片技术的安全计算框架PiRATE。为了证明提出的PiRATE的可行性，我们实施了一个原型。案例研究显示了拟议的PiRATE如何促进分布式学习。最后，我们还基于提出的拜占庭式弹性学习框架，预见了一些未解决的问题和挑战。