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Artificial Intelligence/ Machine Learning in IoT for Authentication and Authorization of Edge Devices

机译:物联网中的人工智能/机器学习,用于边缘设备的身份验证和授权

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Internet of Things (IoT) is progressing at a fast pace. Issues of security and privacy, emerged with introduction of IoT in late nineties, are still amongst the main challenges. In security issues, authentication and authorization of edge devices are main concerns due to resource constrained nature of edge devices. Various solutions have been proposed in the past to address said concerns but most of the solutions are based on increasing the computational capacity, storage and power in edge devices. However, said solutions are not practical since these solutions are either not possible due to small size of edge devices of IoT or not economical for their wide spread adoption. Some of the solutions also suggest the use of light weight cryptographic primitives. However, same are also not practical since all edge devices do not have requisite resources to implement these solutions. This paper proposes use of Artificial Intelligence (AI)/ machine learning in addressing the issues of authentication and authorization in edge devices. Proposed solution is based on fog computing model within a framework of a smart house but without reliance on computational capacity, storage or power of edge devices.
机译:物联网(IoT)的发展速度很快。九十年代末随着物联网的引入而出现的安全和隐私问题仍然是主要挑战之一。在安全问题中,由于边缘设备的资源受限性质,边缘设备的身份验证和授权是主要关注的问题。过去已经提出了各种解决方案来解决上述问题,但是大多数解决方案都基于增加边缘设备中的计算能力,存储和功率。但是,所述解决方案不切实际,因为这些解决方案要么由于物联网边缘设备的尺寸小而无法使用,要么因其广泛采用而不经济。一些解决方案还建议使用轻量级密码原语。但是,由于所有边缘设备都没有实现这些解决方案所必需的资源,因此这也是不切实际的。本文提出使用人工智能(AI)/机器学习解决边缘设备中的身份验证和授权问题。提出的解决方案基于智能房屋框架内的雾计算模型,但不依赖于边缘设备的计算能力,存储或功能。

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