无线传感器网络中基于聚类的低能量自适应聚类算法

Q4 Physics and Astronomy
Divya Kapil
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引用次数: 0

摘要

:无线传感器网络(WSN)对于各种应用至关重要,如监控、工业自动化和环境监测。然而,无线传感器网络的分布式和资源受限设计使其面临许多安全风险,如灰洞攻击。灰洞攻击会导致敌对节点选择性地丢弃或修改数据包,从而导致网络中断和数据完整性受损。为了对抗无线传感器网络中的灰洞攻击,我们在本研究中提出了基于聚类的低能量自适应聚类层次(LEACH)算法。为了提高无线传感器网络的安全性和能效,该方法利用了动态集群形成、高效路由和基于信任的数据包转发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cluster-based Low-Energy Adaptive Clustering Hierarchy for Grayhole Attack in Wireless Sensor Networks
: Wireless sensor networks (WSNs) are essential for a variety of applications, such as surveillance, industrial automation, and monitoring of the environment. The distributed and resource-constrained design of WSNs, however, leaves them open to a number of security risks, such as grayhole attacks. Grayhole attacks cause network interruption and compromised data integrity by causing hostile nodes to selectively drop or modify data packets. To counteract grayhole attacks in WSNs, we suggest the cluster-based low-energy adaptive clustering hierarchy (LEACH) algorithm in this study. To improve the security and energy efficiency of WSNs, the suggested method makes use of dynamic cluster formation, energy-efficient routing, and trust-based packet forwarding.
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来源期刊
NeuroQuantology
NeuroQuantology NEUROSCIENCES-
自引率
0.00%
发文量
355
审稿时长
3 months
期刊介绍: Information not localized
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