期刊
SUSTAINABILITY
卷 14, 期 20, 页码 -出版社
MDPI
DOI: 10.3390/su142013635
关键词
artificial intelligence; cyber security; IoT; evolutionary algorithms; optimisation techniques
资金
- Deanship of Scientific Research at Umm Al-Qura University [22UQU4281768DSR07]
This research proposes an extended form of differential evolution (DE) with an intelligent mutation operator to protect the large volume of data produced by internet systems from unauthorized users and devices. Experimental findings show that this method outperforms the recent evolutionary algorithm (EA) in terms of confidentiality, integrity, authentication, and availability.
The usage of the Internet increased dramatically during the start of the twenty-first century, entangling the system with a variety of services, including social media and e-commerce. These systems begin producing a large volume of data that has to be secured and safeguarded from unauthorised users and devices. In order to safeguard the information of the cyber world, this research suggests an expanded form of differential evolution (DE) employing an intelligent mutation operator with an optimisation-based design. It combines a novel mutation technique with DE to increase the diversity of potential solutions. The new intelligent mutation operator improves the security, privacy, integrity, and authenticity of the information system by identifying harmful requests and responses and helping to defend the system against assault. When implemented on an e-commerce application, the performance of the suggested technique is assessed in terms of confidentiality, integrity, authentication, and availability. The experimental findings show that the suggested strategy outperforms the most recent evolutionary algorithm (EA).
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据