With the explosive growth of data generated by the Internet of Things (IoT) devices, the traditional cloud computing model by\ntransferring all data to the cloud for processing has gradually failed to meet the real-time requirement of IoT services due to high\nnetwork latency. Edge computing (EC) as a new computing paradigm shifts the data processing from the cloud to the edge nodes\n(ENs), greatly improving the Quality of Service (QoS) for those IoT applications with low-latency requirements. However,\ncompared to other endpoint devices such as smartphones or computers, distributed ENs are more vulnerable to attacks for\nrestricted computing resources and storage. In the context that security and privacy preservation have become urgent issues for\nEC, great progress in artificial intelligence (AI) opens many possible windows to address the security challenges. The powerful\nlearning ability of AI enables the system to identify malicious attacks more accurately and efficiently. Meanwhile, to a certain\nextent, transferring model parameters instead of raw data avoids privacy leakage. In this paper, a comprehensive survey of the\ncontribution of AI to the IoTsecurity in EC is presented. First, the research status and some basic definitions are introduced. Next,\nthe IoT service framework with EC is discussed. The survey of privacy preservation and blockchain for edge-enabled IoT services\nwith AI is then presented. In the end, the open issues and challenges on the application of AI in IoT services based on EC\nare discussed.
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