Search - intrusion detection using data mining

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[AI-NN-PR] paper DL : 0: 关联规则论文： GP在入侵检测规则提取中的适应度函数设计.pdf 采用数据挖掘的入侵检测技术研究.pdf 分类规则挖掘算法综述.pdf -Articles of Association Rules: GP in intrusion detection rule extraction in the design of fitness function. Pdf intrusion detection using data mining technology research. Pdf Classification Rule Mining Algorithm. Pdf
Update : 2025-02-17 Size : 1.25mb Publisher : yxm
[Industry research] UsingDataMiningTechniquesforDetectingTerrorRelate DL : 0: An innovative knowledge-based methodology for terrorist detection by using Web traffic content as the audit information is presented. The proposed methodology learns the typical behavior of terrorists by applying a data mining algorithm to the textual content of terror-related Web sites. The resulting profile is used by the system to perform real-time detection of users suspected of being engaged in terrorist activities. The Receiver-Operator Characteristic (ROC) analysis shows that this methodology can outperform a commandbased intrusion detection system
Update : 2025-02-17 Size : 212kb Publisher : keerthi
[Windows Develop] AttacksClassificationinAdaptivIntrusion DL : 0: Recently, information security has become a key issue in information technology as the number of computer security breaches are exposed to an increasing number of security threats. A variety of intrusion detection systems (IDS) have been employed for protecting computers and networks from malicious network-based or host-based attacks by using traditional statistical methods to new data mining approaches in last decades. However, today s commercially available intrusion detection systems are signature-based that are not capable of detecting unknown attacks. In this paper, we present a new learning algorithm for anomaly based network intrusion detection system using decision tree algorithm that distinguishes attacks from normal behaviors and identifies different types of intrusions. Experimental results on the KDD99 benchmark network intrusion detection dataset demonstrate that the proposed learning algorithm achieved 98 detection rate (DR) in comparison with other existing methods.-Recently, information security has become a key issue in information technology as the number of computer security breaches are exposed to an increasing number of security threats. A variety of intrusion detection systems (IDS) have been employed for protecting computers and networks from malicious network-based or host-based attacks by using traditional statistical methods to new data mining approaches in last decades. However, today s commercially available intrusion detection systems are signature-based that are not capable of detecting unknown attacks. In this paper, we present a new learning algorithm for anomaly based network intrusion detection system using decision tree algorithm that distinguishes attacks from normal behaviors and identifies different types of intrusions. Experimental results on the KDD99 benchmark network intrusion detection dataset demonstrate that the proposed learning algorithm achieved 98 detection rate (DR) in comparison with other existing methods.
Update : 2025-02-17 Size : 305kb Publisher : keerthi
[SCM] DMPAGENTS DL : 0: In recent years and within the intrusion detection domain, an increasingly evident trend has emerged. The trend stands within the crossroads of multi-agent systems and data mining. The documents present some related works introducing distributed intrusion detection architectures using the multi-agent design methodology and the data mining techniques.-In recent years and within the intrusion detection domain, an increasingly evident trend has emerged. The trend stands within the crossroads of multi-agent systems and data mining. The documents present some related works introducing distributed intrusion detection architectures using the multi-agent design methodology and the data mining techniques.
Update : 2025-02-17 Size : 6.22mb Publisher : i
[DataMining] IJETAE_0313_100 DL : 0: Intrusion Detection System Using Data Mining Technique: Support Vector Machine
Update : 2025-02-17 Size : 469kb Publisher : salem