异构物联网环境下轻量级加密算法的性能评估

Mounika Jammula, V. V. Mani, Sai Krishna Kondoju
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引用次数: 5

摘要

物联网(internet of things, IoT)是一种先进的智能基础设施,由多个自组织设备组成。在这里,这些设备被用来检查网络并通过互联网传输重要信息。在这个庞大的网络中,未知设备可以制造各种攻击,因此数据的安全性和隐私性是主要关注的问题。物联网网络的主要限制是设备是电池供电的,因此它们可以存储低内置资源。因此,有必要确定更多的资源优化和安全相关的解决方案来解决网络中产生的问题。此外,由于需要维护复杂的加密算法,设备的资源正在以更高的速度消耗。此外,有必要确定适合自动化物联网网络的加密程序以及数据完整性。因此,本文旨在详细介绍各种加密方法及其操作行为,如非对称密钥加密(AKC)和对称密钥加密(SKC)。本次调查主要针对各种攻击的加密方法,如伪造和选择密文,拒绝服务;回放人在中间,键重置,设备捕获和暴力攻击。因此,轻量级加密(LWC)是利用深度学习方法减轻所有这些攻击的突出解决方案,并且可以在物联网环境中以较低的资源利用率保持较高的安全标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Evaluation of Lightweight Cryptographic Algorithms for Heterogeneous IoT Environment
Internet-of-Things (IoT) is an advanced intelligent infrastructure, which is formed by using multiple self-organizing devices. Here, the devices are utilized to examine the network and transfers the important information over internet. In this huge network, the unknown devices can create various attacks, thus the security and privacy of data is the major concerns. The major limitation in the IoT network is the devices are battery powered, so they can store low inbuilt resources. Thus, it is necessary to identify more resource optimized and security related solutions to address the problems generated in the network. In addition, the resources of the devices are consuming in higher speed due to the complex cryptography algorithms to maintain. Further, it is necessary to identify the suitable cryptography procedure for an automated IoT network along with data integrity. Therefore, this article aims to introduce the detailed survey on various cryptographic methods with their operational behavior such as asymmetric key cryptography (AKC) and symmetric key cryptography (SKC). This survey mainly focused on the cryptographic methods with respect to various attacks such as forgery and chosen-cipher text, denial of service; replay man-in-the middle, key reset, device capture and brute force attacks. Hence, the lightweight cryptography (LWC) is the prominent solution to mitigate all these attacks by using the deep learning methods and can maintain the higher security standards with the lower resource utilization in IoT environment.
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