arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2109.02695cs.CR
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基于机器学习的IoT安全认证方案综述

IoT Security and Authentication schemes Based on Machine Learning: Review

Rushit Dave

摘要:

随着技术的最新发展,越来越多的人依靠他们的私人设备来保存他们的敏感信息。与此同时,这些小工具所连接的环境变得更加动态和复杂。这就开启了一个对话,即这些小工具中使用的现代身份验证策略是否可靠,足以保护这些用户的记录安全。本文研究了不同的消费者身份验证方案,提出了更大的保护特殊设备。本文将分为两种讨论同时使用行为生物识别技术和物理层身份验证的身份验证方案。本调查将讨论计算设备的准确性、可用性和标准保护所带来的好处和挑战,以了解这些身份验证系统中的策略。本文的目标是通过展示当今的几个认证模型、它们的原理图和它们的结果来增强这个主题中的附加查找。

英文摘要:

With the latest developments in technology, extra and extra human beings depend on their private gadgets to keep their touchy information. Concurrently, the surroundings in which these gadgets are linked have grown to grow to be greater dynamic and complex. This opens the dialogue of if the modern day authentication strategies being used in these gadgets are dependable ample to preserve these user's records safe. This paper examines the distinct consumer authentication schemes proposed to make bigger the protection of exceptional devices. This article is break up into two one of a kind avenues discussing authentication schemes that use both behavioral biometrics or physical layer authentication. This survey will talk about each the blessings and challenges that occur with the accuracy, usability, and standard protection of computing device getting to know strategies in these authentication systems. This article targets to enhance in addition lookup in this subject via exhibiting the more than a few present day authentication models, their schematics, and their results.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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