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Intrusion detection system using Bagging Ensemble Selection

机译：使用袋装集合选择的入侵检测系统

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For a past few decades, there has been quick progress in internet based applications and technology in the area of computer networks. Data is most important asset of any organization and they require proper protection and management of private and highly sensitive information. Nowadays cyber-attacks have become very common and network security can be provided with Detection Systems. An intrusion detection system analyzes and gathers information from various areas within a network or computer to identify possible security breaches, which include both misuse and intrusion. Researchers are interested in intrusion detection system using data mining techniques as a deceitful skill. This paper aims to give an intrusion detection system using Bagging Ensemble Selection. Bagging Ensemble Selection implementation is fairly straightforward, and it gives an excellent predictive performance on practical problems.
机译：在过去的几十年里，在计算机网络领域的基于互联网的应用和技术方面存在快速进展。数据是任何组织的最重要资产，他们需要正确保护和管理私有和高度敏感的信息。如今网络攻击已成为非常常见的并且可以提供网络安全性检测系统。入侵检测系统分析和收集来自网络或计算机内的各个区域的信息，以识别可能的安全漏洞，包括误用和侵扰。研究人员对使用数据挖掘技术作为欺骗性技能的入侵检测系统感兴趣。本文旨在使用袋装集合选择提供入侵检测系统。袋装集合选择实施相当简单，它对实际问题提供了出色的预测性能。

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