Main Article Content
The Internet of Things (IoT) has significant influences on the development of a vast number of smart objects. However, looking at IoT from another angle, IoT is such a cross-cutting environment operated by several elements, so it poses threats to the security of IoT devices which the existing approaches are unable to solve. Thus, the enhanced editions of the existing methods are required to secure IoT systems appropriately. This paper aims to provide a thorough insight into Deep learning (DL) algorithms’ contributions for IoT security, especially on the ways they operate, the benefits and drawbacks and possible applications in IoT security systems as well as illustrates how they are applied to enhance IoT security. These features can be considered as the orientation for the future developments of hi-tech world. Surveying DL applications in IoT security contributes greatly to researching, constructing, training and evaluating models without the waste of time for IoT systems.
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