Risk assessment model of Internet of Things based on BP neural network algorithm

W. Yan
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Abstract

The internet of things (IOT) is a novel concept. With the rapid development of wireless communication technology, it has quickly become a hot topic. Its basic concept is to communicate, communicate and cooperate with each other around all kinds of things and objects around us through the unique address mode in the world, so as to achieve the common goal. Through in-depth research and investigation, it is found that at present, most banks in China generally adopt the scoring system for personal credit risk assessment (RBI), and the assessment indicators have not kept pace with the times for many years, and basically there is no big change. Obviously, this evaluation method is highly subjective, and the evaluation indicators are relatively backward, slightly rigid and single. In this regard, this paper studies the relatively mature evaluation criteria and methods in the field of information security, and analyzes the information security status of small IOT systems. Integrate the information security features of the IOT to construct a RBI index system for small IOT systems.
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基于BP神经网络算法的物联网风险评估模型
物联网(IOT)是一个新颖的概念。随着无线通信技术的飞速发展,它迅速成为一个热门话题。它的基本概念是通过世界上特有的称呼方式,围绕着我们周围的各种事物和对象相互沟通、沟通和合作,从而达到共同的目的。通过深入的研究和调查发现,目前国内大多数银行普遍采用个人信用风险评估(RBI)计分制度,考核指标多年来没有与时俱进,基本没有大的变化。显然,这种评价方法主观性强,评价指标相对落后,略显僵化和单一。为此,本文研究了信息安全领域较为成熟的评价标准和方法,并对小型物联网系统的信息安全现状进行了分析。结合物联网的信息安全特点,构建小型物联网系统的RBI指标体系。
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