發(fā)布時(shí)間：2018-02-08 13:30

  本文關(guān)鍵詞： 網(wǎng)絡(luò)安全 入侵檢測(cè) 關(guān)聯(lián)規(guī)則 數(shù)據(jù)挖掘　出處：《現(xiàn)代電子技術(shù)》2017年09期 　論文類型：期刊論文

【摘要】：為了有效解決當(dāng)前網(wǎng)絡(luò)入侵檢測(cè)算法存在的缺陷,提高網(wǎng)絡(luò)的安全性,提出基于模糊關(guān)聯(lián)規(guī)則挖掘的網(wǎng)絡(luò)入侵檢測(cè)算法。首先收集網(wǎng)絡(luò)數(shù)據(jù),提取網(wǎng)絡(luò)入侵行為的特征;然后采用模糊關(guān)聯(lián)規(guī)則算法對(duì)入侵行為特征進(jìn)行挖掘,選擇入侵行為最有效的特征,減少特征之間的關(guān)聯(lián)度;最后支持向量機(jī)根據(jù)"一對(duì)多"的思想建立網(wǎng)絡(luò)入侵檢測(cè)的分類器,以KDD CUP數(shù)據(jù)為例對(duì)網(wǎng)絡(luò)入侵檢測(cè)性能進(jìn)行分析。結(jié)果表明,該算法的網(wǎng)絡(luò)入侵檢測(cè)正確率超過(guò)了95%,檢測(cè)結(jié)果要明顯好于其他檢測(cè)算法,易實(shí)現(xiàn),可以用于大規(guī)模網(wǎng)絡(luò)的在線入侵檢測(cè)分析。
[Abstract]:In order to effectively solve the shortcomings of current network intrusion detection algorithms and improve the network security, a network intrusion detection algorithm based on fuzzy association rule mining is proposed. Firstly, the network data is collected to extract the characteristics of network intrusion behavior. Then the fuzzy association rule algorithm is used to mine the intrusion behavior feature, and the most effective feature is selected to reduce the correlation degree between the features. Finally, support vector machine (SVM) constructs a classifier for network intrusion detection based on the idea of "one-to-many". Taking KDD CUP data as an example, the performance of network intrusion detection is analyzed. The results show that, The network intrusion detection accuracy of this algorithm is over 95, and the detection result is obviously better than other detection algorithms. It is easy to implement and can be used for on-line intrusion detection and analysis of large-scale networks.
【作者單位】： 百色學(xué)院信息工程學(xué)院;
【分類號(hào)】：TP393.08;TP311.13

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