检索结果-南通市图书馆

Received Power Based Unmanned Aerial Vehicles (UAVs) Jamming Detection and Nodes Classification Using Machine Learning

引用

Computers, Materials & Continua 2023年第4期75卷 1253-1269页

作者： waleed aldosari Department of Computer Engineering College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia

This paper presents a machine-learning method for detecting jamming UAVs and classifying nodes during jamming attacks onWireless Sensor Networks(WSNs).Jamming is a type of Denial of Service(DoS)attack and intentional interference where a malicious node transmits a high-power signal to increase noise on the receiver side to disrupt the communication channel and reduce performance *** defend and prevent such attacks,the first step is to detect *** current detection approaches use centralized techniques to detect jamming,where each node collects information and forwards it to the base *** a result,overhead and communication costs *** this work,we present a jamming attack and classify nodes into different categories based on their location to the jammer by employing a single node *** a result,we introduced a machine learning model that uses distance ratios and power received as features to detect such ***,we considered several types of jammers transmitting at different power levels to evaluate the proposed metrics using *** a detection accuracy of 99.7%for the k-nearest neighbors(KNN)algorithm and average testing accuracy of 99.9%,the presented solution is capable of efficiently and accurately detecting jamming attacks in wireless sensor networks.

关键词： Jamming attacks machine learning unmanned aerial vehicle(UAV) WSNs

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Localizing Jammer in an Indoor Environment by Estimating Signal Strength and Kalman Filter

引用

Wireless Engineering and Technology 2018年第2期9卷 20-33页

作者： waleed aldosari Mohamed Zohdy School of Engineering and Computer Science Oakland University Rochester Hills USA

Localizing a jammer in an indoor environment in wireless sensor networks becomes a significant research problem due to the ease of blocking the communication between legitimate nodes. An adversary may emit radio frequency to prevent the transmission between nodes. In this paper, we propose detecting the position of the jammer indoor by using the received signal strength and Kalman filter (KF) to reduce the noise due to the multipath signal caused by obstacles in the indoor environment. We compare our work to the Linear Prediction Algorithm (LP) and Centroid Localization Algorithm (CL). We observed that the Kalman filter has better results when estimating the distance compared to other algorithms.

关键词： Jammer Detecting Kalman Filter (KF) Linear Prediction (LP) Centroid Localization (CL) Jammer Received Signal Strength (JRSS) Multipath Signal Indoor Location

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：