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[File Operate456123

Description: 基于数据挖掘的入侵检测系统的设计与实现 基于数据挖掘的入侵检测系统的设计与实现-Based on Data Mining Intrusion Detection System Design and Implementation Based on Data Mining Intrusion Detection System Design and Implementation
Platform: | Size: 59540 | Author: Jihong | Hits:

[Exploitdminid

Description: 入侵检测中的数据挖掘方法研究.pdf-A Research into Data Mining Technology in Intrusion Detection. file type pdf
Platform: | Size: 613768 | Author: 赵艳 | Hits:

[Exploit基于数据挖掘技术入侵检测系统研究

Description: 入侵检测技术已经成为网络安全领域的研究热点。本文介绍了入侵检测的分类以及应用在入侵检测中的数据挖掘方法,并阐述了构建的基于数据挖掘技术的入侵检测系统的设计与实现。-Intrusion Detection Technology network security has become a hot topic. This paper introduces the intrusion detection and the application of the classification in Intrusion Detection Data Mining Methods and expounded on the data mining technology based Intrusion Detection System Design and Implementation.
Platform: | Size: 6753 | Author: 李显 | Hits:

[Internet-Networkdminid

Description: 入侵检测中的数据挖掘方法研究.pdf-A Research into Data Mining Technology in Intrusion Detection. file type pdf
Platform: | Size: 613376 | Author: 赵艳 | Hits:

[File Format456123

Description: 基于数据挖掘的入侵检测系统的设计与实现 基于数据挖掘的入侵检测系统的设计与实现-Based on Data Mining Intrusion Detection System Design and Implementation Based on Data Mining Intrusion Detection System Design and Implementation
Platform: | Size: 59392 | Author: Jihong | Hits:

[Internet-Networkdatamining

Description: 数据挖掘在入侵检测中的应用-Data Mining in Intrusion Detection
Platform: | Size: 41984 | Author: chen | Hits:

[Software Engineeringids

Description: 一篇论文,介绍有关基于数据挖掘的入侵检测系统设计方面的内容-A paper on data mining-based intrusion detection system design aspects
Platform: | Size: 154624 | Author: sifhay | Hits:

[Windows DevelopApriori

Description: 关联规则挖掘的研究工作主要包括:Apriori算法的扩展、数量关联规则挖掘、关联规则增量式更新、无须生成候选项目集的关联规则挖掘、最大频繁项目集挖掘、约束性关联规则挖掘以及并行及分布关联规则挖掘算法等,其中快速挖掘与更新频繁项目集是关联规则挖掘研究的重点,也是多种数据挖掘应用中的技术关键,已用于分类规则挖掘和网络入侵检测等方面的研究。研究者还对数据挖掘的理论进行了有益的探索,将概念格和粗糙集应用于关联规则挖掘中,获得了显著的效果。到目前为止,关联规则的挖掘已经取得了令人瞩目的成绩,包括:单机环境下的关联规则挖掘算法;多值属性关联规则挖掘;关联规则更新算法;基于约束条件的关联规则挖掘;关联规则并行及分布挖掘算法等。-Association rule mining research work include: Apriori algorithm for the expansion of the number of association rules mining, incremental updating of association rules, there is no need to generate candidate itemsets of association rule mining, maximal frequent itemsets mining, association rule mining binding, as well as parallel and Distribution of association rule mining algorithm, one of the rapid mining frequent itemsets and updating of association rules mining are the focus of the study, but also a variety of data mining technology in key applications, has been used in classification rules mining and network intrusion detection studies. The researchers also carried out the theory of data mining has made useful explorations, to concept lattice and rough sets in association rule mining applied to obtain significant results. So far, the mining association rules has made remarkable achievements, including: stand-alone environment for mining association rules algorithm many associatio
Platform: | Size: 2056192 | Author: henry | Hits:

[Software EngineeringDMIDS

Description: 基于数据挖掘技术的入侵检测系统的设计思路与模型,以及改进思路-Based on Data Mining Intrusion Detection System Design and model, as well as ideas to improve
Platform: | Size: 261120 | Author: CCLK | Hits:

[AI-NN-PRpaper

Description: 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
Platform: | Size: 1308672 | Author: yxm | Hits:

[AI-NN-PRResearch_on_Network_intrusion_detection_based_on_d

Description: 本文提出一种基于数据挖掘的入侵检测模型,其主要思想是利用数据挖掘的方法,从经预处理的包含网络连接信息的 审计数据中提取能够区分正常和入侵的规则,并用来检测入侵行为。对Apriori 算法中求频繁集时扫描数据库I/O 负载惊人 的问题提出了一种改进办法。为验证该算法的可行性,文章最后实现了该入侵检测模型的知识库中正常连接规则的挖掘。实 验表明该模型能提取特征生成新规则,并证明了方法的可行性和有效性。-In this paper an intrusion detection system based on data mining is proposed, and its main idea is to apply data mining methods to learn rules that can capture normal and intrusion activities from pre- processed audit data that contain network connection information. Put forward a method to improve the Apriori algorithm, whose I/O is quite surprising when scanning the database. To improve the method is feasible the normal rules in the knowledge database in IDS are mined. And the experiment indicates that the model can produce new rules, which approve the validity and the feasibility of the IDS.
Platform: | Size: 207872 | Author: youby | Hits:

[Industry researchUsingDataMiningTechniquesforDetectingTerrorRelate

Description: 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
Platform: | Size: 217088 | Author: keerthi | Hits:

[Windows DevelopAttacksClassificationinAdaptivIntrusion

Description: 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.
Platform: | Size: 312320 | Author: keerthi | Hits:

[SCMDataMiningTechniquesfor(Network)Intrusion

Description: In Information Security, intrusion detection is the act of detecting actions that attempt to compromise the confidentiality, integrity or availability of a resource. Intrusion detection does not, in general, include prevention of intrusions. In this paper, we are mostly focused on data mining techniques that are being used for such purposes. We debate on the advantages and disadvantages of these techniques. Finally we present a new idea on how data mining can aid IDSs.
Platform: | Size: 372736 | Author: keerthi | Hits:

[Windows DevelopFuzzyIntrusionDetectionSystemviaDataMining

Description: There are two main approaches for implementing IDS Host based and Network based. While the former is implemented in form of software deployed on a host, the latter, usually is built as a hardware product with its own hardware platform (IDS appliance). In this paper, a host based intrusion detection system, that uses the idea of tracing system calls, is introduced. As a program runs, it uses the services of the underlying operating system to do some system calls. This system does not exactly need to know the program codes of each process. Normal and intrusive behaviors are collected with gathering the sequences of system calls for each process. Analysis of data is done via data mining and fuzzy techniques. Data mining is used to extract normal behaviors (normal unique rules) and Fuzzy to enhance intelligence of the System. The proposed system is shown to improve the performance, and decrease size of database, time complexity, and rate of false alarms.-There are two main approaches for implementing IDS Host based and Network based. While the former is implemented in form of software deployed on a host, the latter, usually is built as a hardware product with its own hardware platform (IDS appliance). In this paper, a host based intrusion detection system, that uses the idea of tracing system calls, is introduced. As a program runs, it uses the services of the underlying operating system to do some system calls. This system does not exactly need to know the program codes of each process. Normal and intrusive behaviors are collected with gathering the sequences of system calls for each process. Analysis of data is done via data mining and fuzzy techniques. Data mining is used to extract normal behaviors (normal unique rules) and Fuzzy to enhance intelligence of the System. The proposed system is shown to improve the performance, and decrease size of database, time complexity, and rate of false alarms.
Platform: | Size: 710656 | Author: keerthi | Hits:

[AI-NN-PRwangluoanquan

Description: 基于数据挖掘的智能入侵检测系统研究,提出了一个基于数据挖掘、Agent技术的入侵检测系统框架-Intelligent data mining-based intrusion detection system, proposed based on data mining, Agent Intrusion Detection System
Platform: | Size: 101376 | Author: shenren | Hits:

[matlabIntrusion-Detection

Description: The problem of intrusion detection has been studied and received a lot of attention in machine learning and data mining in the literature survey. The existing techniques are not effective to improve the classification accuracy and to reduce high false alarm rate. Therefore, it is necessary to propose new technique for IDS. In this work, we propose a new K-means clustering method with a different Preprocessing and Genetic Algorithm for identifying intrusion and classification for both anomaly and misuse. The experiments of the proposed IDS are performed with KDD cup’99 data set. The experiments will clearly results the proposed method provides better classification accuracy over existing method.
Platform: | Size: 400384 | Author: Sumit | Hits:

[Other21-20-03082014-Efficient-Data-Mining-Techniques-t

Description: This paper gives the description of various data mining techniques that are used to enhance the performance of the Intrusion detection system.
Platform: | Size: 97280 | Author: deepa | Hits:

[Other3

Description: 本文围绕入侵检测系统进行了深入细致的研究,介绍了入侵检测的研究进展, 分析了入侵检测系统的特征、结构和分类,分析了入侵检测系统的发展方向以及 在入侵检测中常用的数据挖掘方法,深入研究了聚类技术在入侵检测系统中的应 用,并对系统性能做出评估-This paper focuses on the intrusion detection system has been studied intensively, research progress intrusion detection, Analysis of the characteristics, structure and classification of intrusion detection system, analyzes the development direction of intrusion detection systems and Commonly used in intrusion detection data mining method, in-depth study of clustering technology in Intrusion Detection System Use, and assess system performance
Platform: | Size: 993280 | Author: 路粮户 | Hits:

[Software Engineering31-Mining-network-data-for-intrusion-detection-th

Description: Mining network data for intrusion detection through combining SVM with ant colony
Platform: | Size: 687104 | Author: Samir | Hits:
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