首页> 外文期刊>International Journal of Computer Trends and Technology >A Review of Cyber Attack Classification Technique Based on Data Mining and Neural Network Approach
【24h】

A Review of Cyber Attack Classification Technique Based on Data Mining and Neural Network Approach

机译:基于数据挖掘和神经网络方法的网络攻击分类技术综述

获取原文
       

摘要

Cyber attack detection and classification is major challenge for web and network security. The increasing data traffic in network and web invites multiple cyber attack. The dynamic nature and large number of attribute of cyber data faced a problem of detection and prevention. In current research trend various method and framework are proposed by different authors. These framework and proposed method is based on data mining and neural network approach. Data mining offers various techniques such as clustering, classification, rule generation and temporal event mining; these techniques are very efficient for detection process of cyber attack. The application of neural network in cyber attack classification use as feature reduction technique. Feature reduction is very important task in cyber attack classification; because the cyber attack data consists of huge amount of features. This paper presents various method of cyber attack detection and classification technique based on data mining and neural network approach along with IDS evaluation criteria and dataset used for validated of IDS is also discussed here.
机译:网络攻击检测和分类是Web和网络安全的主要挑战。网络和Web中不断增长的数据流量引发了多种网络攻击。网络数据的动态性质和大量属性面临着检测和预防的问题。在当前的研究趋势中,不同的作者提出了各种方法和框架。这些框架和提出的方法是基于数据挖掘和神经网络的方法。数据挖掘提供了多种技术,例如聚类,分类,规则生成和时间事件挖掘。这些技术对于检测网络攻击过程非常有效。神经网络在网络攻击分类中的应用作为特征约简技术。特征减少是网络攻击分类中非常重要的任务。因为网络攻击数据包含大量功能。本文介绍了基于数据挖掘和神经网络方法的各种网络攻击检测和分类技术,以及IDS评估标准和用于IDS验证的数据集。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号