Edge computing has become a practical way to reduce latency and enable real-time decision-making. Running AI models on edge devices can lead to significant performance gains, especially in manufacturing, health care, transportation and infrastructure.
However, distributing data across a network of thousands of devices introduces unique security concerns compared to traditional IT environments. For organizations implementing or considering AI for edge networks, understanding security implications is crucial to keep information and operations secure.
This article has been indexed from DZone Security Zone
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