使用基于Jaya优化的遗传算法的物联网环境增强安全框架

Q3 Computer Science
S. Velliangiri, Iwin Thanakumar Joseph, Shanthini Pandiaraj, P. Leela Jancy, Ch. Madhubabu
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引用次数: 1

摘要

物联网采用云网络,存储在云服务器上的数据极易受到各种攻击。根据目前的分析报告,大约23%的物联网设备容易受到攻击。存储在云存储中的数据极易受到攻击,导致经济增长的回调系数为15%。考虑到上述物联网设备的安全性,本文提出了一种结合Jaya算法和遗传算法的框架,以实现物联网网络中入侵的最优检测。JA是一种不需要任何精确控制参数的无参数算法。相比之下,遗传算法是一种元启发式方法,可以为复杂函数产生合理的高质量解决方案。对所提出算法的广泛分析在准确率、召回率和f分等重要参数上产生了更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An enhanced security framework for IoT environment using Jaya optimisation-based genetic algorithm
The internet of things (IoT) employs a cloud network, and the data stored in the cloud servers are highly vulnerable to various attacks. As per the current analysis report, around 23% of IoT devices are prone to attack. The data stored in the cloud storage are highly vulnerable to attacks leading to a pullback factor of 15% in economic growth. Considering the above security of the IoT devices, this paper proposes a framework integrating the Jaya algorithm and genetic algorithm to achieve an optimal detection of intrusion in the IoT network. The JA is a parameter less algorithm that does not require any precise control parameters. In contrast, the GA is a meta-heuristic approach that produces reasonable quality solutions for complex functions. The extensive analysis of the proposed algorithm yield better performance in vital parameters like accuracy, recall and F-score.
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来源期刊
International Journal of Internet Technology and Secured Transactions
International Journal of Internet Technology and Secured Transactions Computer Science-Computer Networks and Communications
CiteScore
2.50
自引率
0.00%
发文量
31
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