基于人工免疫算法和adam Adar的无线传感器网络优化

Shireen Shireen, Dr. Shaheen Ayyub
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引用次数: 0

摘要

随着各种类型的动态网络通过简单的设备开发出来,人们开始以各种方式使用动态网络。这些易受攻击的网络很容易被攻击并进行恶意活动。这项工作开发了一个模型,可以在没有先验信息的动态节点环境中生成从源到目的地的路径。路径生成将采用人工免疫遗传算法,该算法可以在短时间内找到较好的路径。为了检测恶意活动,需要识别这些节点。因此,攻击者节点的识别是通过信任模型来完成的,其中adam Adar信任函数将节点的相互信任值作为节点过去性能的epr。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Immune Algorithm and Adamic Adar based Wireless Sensor Network Optimization
As different types of dynamic networks are developed by easy means of devices, people start using them for various means. Such vulnerable networks are easy places to attack and perform malicious activities. This work develops a model that can generate a path from source to destination in a dynamic node environment without prior information. Path generation artificial immune genetic algorithms will be used, as this algorithms find a good path in a short time. In order to detect the malicious activity, such nodes need to be identified. Hence identification of attackers nodes is done by trust model where Adamic Adar trust function finds the mutual trust value of node as epr past performance of nodes.
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