车联网中基于分割行为特征的入侵检测技术的设计与实现.doc
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车联网中基于分割行为特征的入侵检测技术的设计与实现,2万字自己原创的毕业论文，已经通过校内系统检测，重复率低，仅在本站独家出售，大家放心下载使用摘要 随着车联网研究的进展和其潜在的应用前景，车联网的安全问题正逐渐成为人们关注的焦点。由于车联网中节点高速移动、无线信道质量不稳定等影响，产生了原本在互联网络中不存在的安全问题...
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车联网中基于分割行为特征的入侵检测技术的设计与实现
2万字
自己原创的毕业论文，已经通过校内系统检测，重复率低，仅在本站独家出售，大家放心下载使用
摘要 随着车联网研究的进展和其潜在的应用前景，车联网的安全问题正逐渐成为人们关注的焦点。由于车联网中节点高速移动、无线信道质量不稳定等影响，产生了原本在互联网络中不存在的安全问题，使得原本有效的安全措施失效。为了保证车联网的安全、稳定、高效的运行，解决各种各样的车联网安全问题，仅依赖一些传统防御技术，如防火墙、身份认证、数据加密等一般被动防御方法已经不能做到完全抵御入侵，为此，有必要在车联网中引入入侵检测技术(IDS)。
本文针对车联网的特性，致力于建立适合车联网环境的入侵检测技术。首先，介绍了计算机网络中入侵检测的相关概念，发现了现有入侵检测技术存在不足，并通过分析了神经网络的相关知识，发现神经网络所固有的自适应、自学习等能力很适合入侵检测系统的要求，且能够弥补传统入侵检测技术的不足。然后，还对BP神经网络以及BP学习算法进行了研究，发现BP神经网络具有的特性很符合车联网对于入侵检测的需求。
由于车联网中的数据要求高可靠性和及时性，则车联网中的入侵检测需要快速地检测出入侵行为。为此，将车联网中的事件的行为特征分割成几个特征子集，分别输入到几个神经网络中同时进行检测。在此基础上，本文在车联网的系统模型上设计了一种基于分割行为特征的入侵检测技术方案。该方案给出了一个基于分割行为特征的入侵检测系统的总框架，并就框架中各模块的原理和实现给予了详细的介绍。
最后，利用交通仿真软件VanetMobiSim搭建道路仿真场景，模拟道路上车辆节点的运动轨迹，并将生成的仿真数据作为基准数据集。随机抽取数据集中的部分数据作为训练集和测试集,并将数据作为入侵检测系统的输入，从而检测出方案的性能。
关键词：车联网 入侵检测 神经网络 BP学习算法
Design and implementation of Intrusion detection technology based on segmentation behavior characteristics in VANET
Abstract With the progress of the VANET research and its potential application prospect, the VANET security problem is becoming the focus of attention. As the VANET nodes in high-speed mobile and wireless channel quality of instability and other affect, resulting in a safety problem originally does not exist in the network, making the original effective security measures fail. In order to ensure safe, stable and efficient operation of vehicular ad-hoc network, to solve all kinds of the vehicular ad-hoc network security issues, only rely on traditional defense technologies such as firewalls, identity authentication, data encryption and other methods have been generally passive defense can not be completely resist invasion, Therefore, it is necessary to introduce intrusion detection technology in the VANET.
In this paper, according to the characteristics of the VANET, is committed to establish suitable for the VANET environment of intrusion detection technology. First of all, Introduces the related concepts about intrusion detection, found the shortcomings of existing intrusion detection technology, and through the analysis of the relevant knowledge of the neural network, found that neural network of adaptive and self-learning ability is very suitable for the requirement of the intrusion detection system, and to be able to make up for the inadequacy of the traditional intrusion detection technology. Then, also on the BP neural network and BP learning algorithm is studied, and found that the characteristics of BP neural network has very accord with VANET demand for intrusion detection.
Due to the data in the VANET requires high reliability and timeliness, the intrusion detection in the VANET need to quickly detect the intrusion behavior. So, the features of events in the VANET divided into several subsets, input into several neural network respectively for testing at the same time. On this basis, the paper design a kind of intrusion detection program based on segmentation behavior characteristics on the system model of the VANET. The program gives an intrusion detection system based on segmentation behavior characteristics of total framework, and on the principle and implementation of each module framework to give a detailed introduction.
Finally, by using traffic simulation software VanetMobiSim build road simulation scenarios, simulated trajectories of vehicles on the road nodes, and the generated simulation data as a baseline data set. Part of the data randomly selected as the training data set and test set, and the data as the input of intrusion detection system, so as to detect the performance of the program.
Key words: VANET Intrusion detection Neural network BP learning algorithm
目 录
第一章、绪论 1
1.1、课题研究背景及意义 1
1.2、国内外的研究现状及存在问题 2
1.3、本文的主要研究内容及组织结构 3
1.3.1 本文的主要研究内容 3
1.3.2 本文的组织结构 3
第二章、入侵检测技术 5
2.1、入侵检测技术概述 5
2.1.1 安全的概念 5
2.1.2、入侵的概念 5
2.1.3、入侵检测的概念 5
2.2、入侵检测的发展历程 6
2.3、入侵检测的分类 7
2.3.1 根据检测数据源分类 7
2.3.2 根据检测的分析技术分类 8
2.4、入侵检测通用模型 9
2.5、现有入侵检测技术的不足 10
2.6、本章小结 11
第三章、基于..
2万字
自己原创的毕业论文，已经通过校内系统检测，重复率低，仅在本站独家出售，大家放心下载使用
摘要 随着车联网研究的进展和其潜在的应用前景，车联网的安全问题正逐渐成为人们关注的焦点。由于车联网中节点高速移动、无线信道质量不稳定等影响，产生了原本在互联网络中不存在的安全问题，使得原本有效的安全措施失效。为了保证车联网的安全、稳定、高效的运行，解决各种各样的车联网安全问题，仅依赖一些传统防御技术，如防火墙、身份认证、数据加密等一般被动防御方法已经不能做到完全抵御入侵，为此，有必要在车联网中引入入侵检测技术(IDS)。
本文针对车联网的特性，致力于建立适合车联网环境的入侵检测技术。首先，介绍了计算机网络中入侵检测的相关概念，发现了现有入侵检测技术存在不足，并通过分析了神经网络的相关知识，发现神经网络所固有的自适应、自学习等能力很适合入侵检测系统的要求，且能够弥补传统入侵检测技术的不足。然后，还对BP神经网络以及BP学习算法进行了研究，发现BP神经网络具有的特性很符合车联网对于入侵检测的需求。
由于车联网中的数据要求高可靠性和及时性，则车联网中的入侵检测需要快速地检测出入侵行为。为此，将车联网中的事件的行为特征分割成几个特征子集，分别输入到几个神经网络中同时进行检测。在此基础上，本文在车联网的系统模型上设计了一种基于分割行为特征的入侵检测技术方案。该方案给出了一个基于分割行为特征的入侵检测系统的总框架，并就框架中各模块的原理和实现给予了详细的介绍。
最后，利用交通仿真软件VanetMobiSim搭建道路仿真场景，模拟道路上车辆节点的运动轨迹，并将生成的仿真数据作为基准数据集。随机抽取数据集中的部分数据作为训练集和测试集,并将数据作为入侵检测系统的输入，从而检测出方案的性能。
关键词：车联网 入侵检测 神经网络 BP学习算法
Design and implementation of Intrusion detection technology based on segmentation behavior characteristics in VANET
Abstract With the progress of the VANET research and its potential application prospect, the VANET security problem is becoming the focus of attention. As the VANET nodes in high-speed mobile and wireless channel quality of instability and other affect, resulting in a safety problem originally does not exist in the network, making the original effective security measures fail. In order to ensure safe, stable and efficient operation of vehicular ad-hoc network, to solve all kinds of the vehicular ad-hoc network security issues, only rely on traditional defense technologies such as firewalls, identity authentication, data encryption and other methods have been generally passive defense can not be completely resist invasion, Therefore, it is necessary to introduce intrusion detection technology in the VANET.
In this paper, according to the characteristics of the VANET, is committed to establish suitable for the VANET environment of intrusion detection technology. First of all, Introduces the related concepts about intrusion detection, found the shortcomings of existing intrusion detection technology, and through the analysis of the relevant knowledge of the neural network, found that neural network of adaptive and self-learning ability is very suitable for the requirement of the intrusion detection system, and to be able to make up for the inadequacy of the traditional intrusion detection technology. Then, also on the BP neural network and BP learning algorithm is studied, and found that the characteristics of BP neural network has very accord with VANET demand for intrusion detection.
Due to the data in the VANET requires high reliability and timeliness, the intrusion detection in the VANET need to quickly detect the intrusion behavior. So, the features of events in the VANET divided into several subsets, input into several neural network respectively for testing at the same time. On this basis, the paper design a kind of intrusion detection program based on segmentation behavior characteristics on the system model of the VANET. The program gives an intrusion detection system based on segmentation behavior characteristics of total framework, and on the principle and implementation of each module framework to give a detailed introduction.
Finally, by using traffic simulation software VanetMobiSim build road simulation scenarios, simulated trajectories of vehicles on the road nodes, and the generated simulation data as a baseline data set. Part of the data randomly selected as the training data set and test set, and the data as the input of intrusion detection system, so as to detect the performance of the program.
Key words: VANET Intrusion detection Neural network BP learning algorithm
目 录
第一章、绪论 1
1.1、课题研究背景及意义 1
1.2、国内外的研究现状及存在问题 2
1.3、本文的主要研究内容及组织结构 3
1.3.1 本文的主要研究内容 3
1.3.2 本文的组织结构 3
第二章、入侵检测技术 5
2.1、入侵检测技术概述 5
2.1.1 安全的概念 5
2.1.2、入侵的概念 5
2.1.3、入侵检测的概念 5
2.2、入侵检测的发展历程 6
2.3、入侵检测的分类 7
2.3.1 根据检测数据源分类 7
2.3.2 根据检测的分析技术分类 8
2.4、入侵检测通用模型 9
2.5、现有入侵检测技术的不足 10
2.6、本章小结 11
第三章、基于..
