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: |
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Author:henry |
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Description: 流分类算法中的一种，Scalable Packet Classification 非常有参考价值-Packet classification is important for applications such as
firewalls, intrusion detection, and differentiated services. Existing
algorithms for packet classification reported in the literature
scale poorly in either time or space as filter databases
grow in size. Hardware solutions such as TCAMs do not
scale to large classifiers. However, even for large classifiers
(say 100,000 rules), any packet is likely to match a few (say
10) rules. Our paper seeks to exploit this observation to
produce a scalable packet classification scheme called Aggregated
Bit Vector (ABV). Our paper takes the bit vector
search algorithm (BV) described in [11] (which takes linear
time) and adds two new ideas, recursive aggregation of
bit maps and filter rearrangement, to create ABV (which
can take logarithmic time for many databases). We show
that ABV outperforms BV by an order of magnitude using
simulations on both industrial firewall databases and synthetically
generated databases. Platform: |
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Author:Reguse |
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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: |
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Author:yxm |
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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: |
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Author:Sumit |
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Description: 本文前三章分别简要介绍信息安全，入侵检测和安全日志的相关
概念和基本原理；第四章重点介绍数据挖掘技术，包括了关联规则分
析，序列分析，分类分析和聚类分析；第五章论证数据挖掘技术应用
于入侵检测系统的必要性和实施的系统架构；第六章详细说明实验流
程和实验过程中对关联规则算法的改进，其中重点研究了运用 K-均
值算法对审计日志做预处理和在实现关联规则挖掘时，如何改进
Apriori 算法，使之能在面对安全日志这种高维度数据时比原有算法
效率获得大幅度提高；-This article briefly describes the first three chapters were related to information security, intrusion detection, and security logs
The basic concepts and principles chapter focuses on data mining technology, including a sub-association rules
Analysis, sequence analysis, classification and clustering analysis Chapter demonstrate the application of data mining techniques
On the necessity of the intrusion detection system and system architecture implementation flow experiments described in detail in Chapter VI
Cheng and experiment to improve the algorithm of association rules, which are focused on the use of K-
Value preprocessing algorithm for audit logs and in the realization of association rule mining, the ways to improve
Apriori algorithm, so that it can log in the face of such high-dimensional data security than the original algorithm
Obtain greatly improved efficiency Platform: |
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Author:路粮户 |
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Search - classification algorithm for intrusion detection