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基于logs2intrusions与Web Log Explorer的综合取证分析研究 认领 引用 被引量：1
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作者 杨晶 赵鑫 芦天亮 《信息网络安全》 CSCD 2017年第3期33-38,共6页
随着互联网应用的迅猛增长,其受到的安全威胁也越来越严重,尤其是网络入侵攻击事件造成了极大的危害。目前,对入侵行为检测的一种必要手段是对日志数据进行分析,网站日志文件是记录Web服务器接收处理请求以及运行时错误等各种原始信息... 随着互联网应用的迅猛增长,其受到的安全威胁也越来越严重,尤其是网络入侵攻击事件造成了极大的危害。目前,对入侵行为检测的一种必要手段是对日志数据进行分析,网站日志文件是记录Web服务器接收处理请求以及运行时错误等各种原始信息的文件,但目前来看网络日志文件的作用还有待进一步提升。文章分析了logs2intrusions、Web Log Explorer、光年SEO日志分析系统、逆火网站分析器这四种日志分析工具的特性,提出了基于logs2intrusions和Web Log Explorer两个工具优势的综合取证分析技术,实现了对大批量入侵攻击日志数据的快速分析处理,提高了对网络入侵攻击行为识别的准确率。 展开更多
关键词 网络入侵检测 logs2intrusions WebLogExplorer 系统日志
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Web log classification framework with data augmentation based on GANs 认领 引用 被引量：1
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作者 He Mingshu Jin Lei +1 位作者 Wang Xiaojuan Li Yuan 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2020年第5期34-46,共13页
Attacks on web servers are part of the most serious threats in network security fields.Analyzing logs of web attacks is an effective approach for malicious behavior identification.Traditionally,machine learning models... Attacks on web servers are part of the most serious threats in network security fields.Analyzing logs of web attacks is an effective approach for malicious behavior identification.Traditionally,machine learning models based on labeled data are popular identification methods.Some deep learning models are also recently introduced for analyzing logs based on web logs classification.However,it is limited to the amount of labeled data in model training.Web logs with labels which mark specific categories of data are difficult to obtain.Consequently,it is necessary to follow the problem about data generation with a focus on learning similar feature representations from the original data and improve the accuracy of classification model.In this paper,a novel framework is proposed,which differs in two important aspects:one is that long short-term memory(LSTM)is incorporated into generative adversarial networks(GANs)to generate the logs of web attack.The other is that a data augment model is proposed by adding logs of web attack generated by GANs to the original dataset and improved the performance of the classification model.The results experimentally demonstrate the effectiveness of the proposed method.It improved the classification accuracy from 89.04%to 95.04%. 展开更多
关键词 generative adversarial networks(GANs) web log data augmentation classification
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Data-driven human and bot recognition from web activity logs based on hybrid learning techniques 认领 引用
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作者 Marek Gajewski Olgierd Hryniewicz +5 位作者 Agnieszka Jastrzębska Mariusz Kozakiewicz Karol Opara Jan Wojciech Owsiński Sławomir Zadrozny Tomasz Zwierzchowski 《Digital Communications and Networks》 SCIE CSCD 2024年第4期1178-1188,共11页
Distinguishing between web traffic generated by bots and humans is an important task in the evaluation of online marketing campaigns.One of the main challenges is related to only partial availability of the performanc... Distinguishing between web traffic generated by bots and humans is an important task in the evaluation of online marketing campaigns.One of the main challenges is related to only partial availability of the performance metrics:although some users can be unambiguously classified as bots,the correct label is uncertain in many cases.This calls for the use of classifiers capable of explaining their decisions.This paper demonstrates two such mechanisms based on features carefully engineered from web logs.The first is a man-made rule-based system.The second is a hierarchical model that first performs clustering and next classification using human-centred,interpretable methods.The stability of the proposed methods is analyzed and a minimal set of features that convey the classdiscriminating information is selected.The proposed data processing and analysis methodology are successfully applied to real-world data sets from online publishers. 展开更多
关键词 Web logs Classification Clustering Web traffic Bots Interpretability
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Conceptualizing Mining of Firm's Web Log Files 认领 引用 被引量：1
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作者 Ruangsak TRAKUNPHUTTHIRAK Yen CHEUNG Vincent C.S.LEE 《Journal of Systems Science and Information》 CSCD 2017年第6期489-510,共22页
In this era of a data-driven society, useful data(Big Data) is often unintentionally ignored due to lack of convenient tools and expensive software. For example, web log files can be used to identify explicit informat... In this era of a data-driven society, useful data(Big Data) is often unintentionally ignored due to lack of convenient tools and expensive software. For example, web log files can be used to identify explicit information of browsing patterns when users access web sites. Some hidden information,however, cannot be directly derived from the log files. We may need external resources to discover more knowledge from browsing patterns. The purpose of this study is to investigate the application of web usage mining based on web log files. The outcome of this study sets further directions of this investigation on what and how implicit information embedded in log files can be efficiently and effectively extracted. Further work involves combining the use of social media data to improve business decision quality. 展开更多
关键词 web usage mining web log files Big Data machine learning business intelligence
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基于XGMML-LOGML的Web日志挖掘 认领 引用 被引量：1
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作者 余肖生 《重庆工学院学报（自然科学版）》 2008年第7期61-65,共5页
介绍了XGMML和LOGML语言,在此基础上讨论了Web日志文件的预处理过程和一个基于XGMML-LOGML的Web日志挖掘体系结构,实例表明:与原始日志文件挖掘相比,基于XGMML-LOGML处理的Web日志文件挖掘所需要的时间更少,挖掘的内容质量更高,能更好... 介绍了XGMML和LOGML语言,在此基础上讨论了Web日志文件的预处理过程和一个基于XGMML-LOGML的Web日志挖掘体系结构,实例表明:与原始日志文件挖掘相比,基于XGMML-LOGML处理的Web日志文件挖掘所需要的时间更少,挖掘的内容质量更高,能更好地满足用户的需求. 展开更多
关键词 LOGML XGMML Web日志挖掘
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Research on Web Page Classification Method Based on Query Log 认领 引用
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作者 YE Feiyue MA Yixing 《Journal of Shanghai Jiaotong university(Science)》 EI 2018年第3期404-410,共7页
Web page classification is an important application in many fields of Internet information retrieval,such as providing directory classification and vertical search. Methods based on query log which is a light weight v... Web page classification is an important application in many fields of Internet information retrieval,such as providing directory classification and vertical search. Methods based on query log which is a light weight version of Web page classification can avoid Web content crawling, making it relatively high in efficiency, but the sparsity of user click data makes it difficult to be used directly for constructing a classifier. To solve this problem, we explore the semantic relations among different queries through word embedding, and propose three improved graph structure classification algorithms. To reflect the semantic relevance between queries, we map the user query into the low-dimensional space according to its query vector in the first step. Then, we calculate the uniform resource locator(URL) vector according to the relationship between the query and URL. Finally, we use the improved label propagation algorithm(LPA) and the bipartite graph expansion algorithm to classify the unlabeled Web pages. Experiments show that our methods make about 20% more increase in F1-value than other Web page classification methods based on query log. 展开更多
关键词 Web page classification word embedding query log
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Mining Interesting Knowledge from Web-Log 认领 引用 被引量：1
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作者 ZHOUHong-fang FENGBo-qin +1 位作者 HEIXin-hong LULin-tao 《Wuhan University Journal of Natural Sciences》 EI CAS 2004年第5期569-574,共6页
Web-log contains a lot of information related with user activities on the Internet. How to mine user browsing interest patterns effectively is an important and challengeable research topic. On the analysis of the pres... Web-log contains a lot of information related with user activities on the Internet. How to mine user browsing interest patterns effectively is an important and challengeable research topic. On the analysis of the present algorithm’s advantages and disadvantages we propose a new concept: support-interest. Its key insight is that visitor will backtrack if they do not find the information where they expect. And the point from where they backtrack is the expected location for the page. We present User Access Matrix and the corresponding algorithm for discovering such expected locations that can handle page caching by the browser. Since the URL-URL matrix is a sparse matrix which can be represented by List of 3-tuples, we can mine user preferred sub-paths from the computation of this matrix. Accordingly, all the sub-paths are merged, and user preferred paths are formed. Experiments showed that it was accurate and scalable. It’s suitable for website based application, such as to optimize website’s topological structure or to design personalized services. Key words Web Mining - user preferred path - Web-log - support-interest - personalized services CLC number TP 391 Foundation item: Supported by the National High Technology Development (863 program of China) (2001AA113182)Biography: ZHOU Hong-fang (1976-), female.Ph. D candidate, research direction: data mining and knowledge discovery in databases. 展开更多
关键词 Web Mining user preferred path Web-log support-interest personalized services
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基于Web-log的频繁浏览路径挖掘 认领 引用
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作者 罗超 《信息技术》 2004年第11期4-7,共4页
利用Web日志文件,采用LossyCounting算法对用户频繁浏览路径进行挖掘。在设计中,根据频繁路径挖掘的实际情况对算法进行了优化和改进。实验表明该方法能快速准确地发现用户频繁浏览路径,且具有较好的可扩展性,适用于电子商务网站的站点... 利用Web日志文件,采用LossyCounting算法对用户频繁浏览路径进行挖掘。在设计中,根据频繁路径挖掘的实际情况对算法进行了优化和改进。实验表明该方法能快速准确地发现用户频繁浏览路径,且具有较好的可扩展性,适用于电子商务网站的站点优化和个性化服务等。 展开更多
关键词 数据挖掘 网页日志挖掘 频繁浏览路径
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Fuzzy Clustering Method for Web User Based on Pages Classification 认领 引用 被引量：2
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作者 ZHANLi-qiang LIUDa-xin 《Wuhan University Journal of Natural Sciences》 EI CAS 2004年第5期553-556,共4页
A new method for Web users fuzzy clustering based on analysis of user interest characteristic is proposed in this article. The method first defines page fuzzy categories according to the links on the index page of the... A new method for Web users fuzzy clustering based on analysis of user interest characteristic is proposed in this article. The method first defines page fuzzy categories according to the links on the index page of the site, then computes fuzzy degree of cross page through aggregating on data of Web log. After that, by using fuzzy comprehensive evaluation method, the method constructs user interest vectors according to page viewing times and frequency of hits, and derives the fuzzy similarity matrix from the interest vectors for the Web users. Finally, it gets the clustering result through the fuzzy clustering method. The experimental results show the effectiveness of the method. Key words Web log mining - fuzzy similarity matrix - fuzzy comprehensive evaluation - fuzzy clustering CLC number TP18 - TP311 - TP391 Foundation item: Supported by the Natural Science Foundation of Heilongjiang Province of China (F0304)Biography: ZHAN Li-qiang (1966-), male, Lecturer, Ph. D. research direction: the theory methods of data mining and theory of database. 展开更多
关键词 Web log mining fuzzy similarity matrix fuzzy comprehensive evaluation fuzzy clustering
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Testing and Evaluation for Web Usability Based on Extended Markov Chain Model 认领 引用 被引量：3
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作者 MAOCheng-ying LUYan-sheng 《Wuhan University Journal of Natural Sciences》 EI CAS 2004年第5期687-693,共7页
As the increasing popularity and complexity of Web applications and the emergence of their new characteristics, the testing and maintenance of large, complex Web applications are becoming more complex and difficult. W... As the increasing popularity and complexity of Web applications and the emergence of their new characteristics, the testing and maintenance of large, complex Web applications are becoming more complex and difficult. Web applications generally contain lots of pages and are used by enormous users. Statistical testing is an effective way of ensuring their quality. Web usage can be accurately described by Markov chain which has been proved to be an ideal model for software statistical testing. The results of unit testing can be utilized in the latter stages, which is an important strategy for bottom-to-top integration testing, and the other improvement of extended Markov chain model (EMM) is to present the error type vector which is treated as a part of page node. this paper also proposes the algorithm for generating test cases of usage paths. Finally, optional usage reliability evaluation methods and an incremental usability regression testing model for testing and evaluation are presented. Key words statistical testing - evaluation for Web usability - extended Markov chain model (EMM) - Web log mining - reliability evaluation CLC number TP311. 5 Foundation item: Supported by the National Defence Research Project (No. 41315. 9. 2) and National Science and Technology Plan (2001BA102A04-02-03)Biography: MAO Cheng-ying (1978-), male, Ph.D. candidate, research direction: software testing. Research direction: advanced database system, software testing, component technology and data mining. 展开更多
关键词 statistical testing evaluation for Web usability extended Markov chain model (EMM) Web log mining reliability evaluation
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Semantic Session Analysis for Web Usage Mining 认领 引用 被引量：3
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作者 ZHANG Hui SONG Hantao XU Xiaomei 《Wuhan University Journal of Natural Sciences》 CAS 2007年第5期773-776,共4页
A semantic session analysis method partitioning Web usage logs is presented. Semantic Web usage log preparation model enhances usage logs with semantic. The Markov chain model based on ontology semantic measurement is... A semantic session analysis method partitioning Web usage logs is presented. Semantic Web usage log preparation model enhances usage logs with semantic. The Markov chain model based on ontology semantic measurement is used to identifying which active session a request should belong to. The competitive method is applied to determine the end of the sessions. Compared with other algorithms, more successful sessions are additionally detected by semantic outlier analysis. 展开更多
关键词 Web usage mining Web log preparation session analysis
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Web multimedia information retrieval using improved Bayesian algorithm 认领 引用 被引量：3
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作者 余铁军 陈纯 +1 位作者 余铁民 林怀忠 《Journal of Zhejiang University Science》 2003年第4期415-420,共6页
The main thrust of this paper is application of a novel data mining approach on the log of user' s feedback to improve web multimedia information retrieval performance. A user space model was constructed based on ... The main thrust of this paper is application of a novel data mining approach on the log of user' s feedback to improve web multimedia information retrieval performance. A user space model was constructed based on data mining, and then integrated into the original information space model to improve the accuracy of the new information space model. It can remove clutter and irrelevant text information and help to eliminate mismatch between the page author' s expression and the user' s understanding and expectation. User spacemodel was also utilized to discover the relationship between high-level and low-level features for assigning weight. The authors proposed improved Bayesian algorithm for data mining. Experiment proved that the au-thors' proposed algorithm was efficient. 展开更多
关键词 Relevant feedback Web log mining Improved Bayesian algorithm User space model
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结合网站内容和结构进行的Web日志挖掘 认领 引用 被引量：9
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作者 江宝林 申展 +2 位作者 张川 葛家翔 胡运发 《计算机工程》 EI CAS 北大核心 2004年第16期30-32,共3页
提出一种以聚类为基础的Web日志挖掘方法:从Web日志事务、Web站点内容和Web站点结构3个不同方面来聚类页面集合,并通过将用户的访问记录和页面聚集进行匹配和相关度计算,来预测用户感兴趣的页面。
关键词 Web日志挖掘 Web日志事务 访问模式 聚类
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一种Web用户行为聚类算法 认领 引用 被引量：20
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作者 业宁 李威 +1 位作者 梁作鹏 董逸生 《小型微型计算机系统》 北大核心 2004年第7期1364-1367,共4页
提出了一种新的路径相似度系数计算方法 ,并使之与雅可比相似系数结合 ,用于计算用户访问行为的相似度 ,在此基础之上又提出了一种分析 Web用户行为的聚类算法 (FCC) ,通过挖掘 Web日志 ,找出具有相似行为的 Web用户 .由于 FCC聚类算法... 提出了一种新的路径相似度系数计算方法 ,并使之与雅可比相似系数结合 ,用于计算用户访问行为的相似度 ,在此基础之上又提出了一种分析 Web用户行为的聚类算法 (FCC) ,通过挖掘 Web日志 ,找出具有相似行为的 Web用户 .由于 FCC聚类算法过滤了小于指定阈值的相似度系数 ,大大缩小了数据规模 ,很好地解决了其他聚类算法 (如层次聚类 )在高维空间聚类时的“维数灾难”问题 ,最后的实验结果很好 . 展开更多
关键词 Web日志 数据挖掘 聚类 相似度
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一个简单的Web日志挖掘系统 认领 引用 被引量：23
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作者 杨怡玲 管旭东 +1 位作者 陆丽娜 尤晋元 《上海交通大学学报》 EI CAS 北大核心 2000年第7期932-935,共4页
在分析 Web日志挖掘的困难及对策的基础上 ,给出了一个简单的 Web日志挖掘系统( SWLMS)的体系结构 .具体介绍了 SWLMS中日志的预处理过程 ,包括数据净化、用户识别、会话识别、路径补充的主要任务及其实现 ,并着重介绍了预处理之后的序... 在分析 Web日志挖掘的困难及对策的基础上 ,给出了一个简单的 Web日志挖掘系统( SWLMS)的体系结构 .具体介绍了 SWLMS中日志的预处理过程 ,包括数据净化、用户识别、会话识别、路径补充的主要任务及其实现 ,并着重介绍了预处理之后的序列模式识别过程和算法 ,包括最大向前路径的识别和频繁遍历路径的发现 。 展开更多
关键词 数据挖掘 Web日志挖掘 序列模式识别 SWLMS
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Web日志挖掘技术进展 认领 引用 被引量：17
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作者 陈新中 李岩 +2 位作者 杨炳儒 谢永红 张运涛 《系统工程与电子技术》 EI 北大核心 2003年第4期492-495,共4页
用户访问Internet时,服务器、客户机日志会记录下大量的用户访问信息。通过挖掘这些日志信息所得到的用户访问模式,在个性化信息服务、改进门户站点设计和服务、开展有针对性的电子商务、构建智能化Web站点、提高网站的声誉和效益等方... 用户访问Internet时,服务器、客户机日志会记录下大量的用户访问信息。通过挖掘这些日志信息所得到的用户访问模式,在个性化信息服务、改进门户站点设计和服务、开展有针对性的电子商务、构建智能化Web站点、提高网站的声誉和效益等方面都将起到重要的作用。概述了Web挖掘的概念、分类及其主要应用领域,详细介绍了Web日志挖掘的主要方法和用户访问模式挖掘算法及国内外最新研究进展。最后提出了Web用户访问信息挖掘研究的发展方向和趋势。 展开更多
关键词 AI 万维网 Web挖掘 Web日志挖掘
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Web日志挖掘中的会话识别方法 认领 引用 被引量：14
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作者 周爱武 程博 +1 位作者 李孙长 夏松 《计算机工程与设计》 北大核心 2010年第5期936-938,964,共3页
为更好地实现会话识别,从而为后续模式发现提供准确的挖掘数据,在分析现有常用的会话识别方法后,提出一种基于待挖掘站点首页的用户会话识别方法。该方法根据用户浏览站点的习惯,以站点首页作为用户新会话开始标识,并增强了用户会话的... 为更好地实现会话识别,从而为后续模式发现提供准确的挖掘数据,在分析现有常用的会话识别方法后,提出一种基于待挖掘站点首页的用户会话识别方法。该方法根据用户浏览站点的习惯,以站点首页作为用户新会话开始标识,并增强了用户会话的定义。最后利用数据库编程实现该方法,将识别出的会话存储在数据库中,便于后续数据挖掘使用。实验结果表明,该方法能识别出更多的用户会话,且识别会话的准确率也更高。 展开更多
关键词 数据预处理 Web日志 会话识别 站点首页 数据库
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Web日志文件的异常数据挖掘算法及其应用 认领 引用 被引量：11
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作者 赵泽茂 何坤金 +2 位作者 陈鹏 景雪琴 蒋霞东 《计算机工程》 EI CAS 北大核心 2003年第17期195-196,F003,共2页
从数量化角度给出了异常数据的一般性定义，以Web服务器日志文件数据为依据，讨论了挖掘异常数据的方法和途径；给出了基于距离的单指标的离散统计法和综合统计法，并结合校园网作了实际的分析处理。结果表明，该方法是可行的。
关键词 异常数据 数据挖掘 Web日志 上网行为模式
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Web日志挖掘中的数据预处理技术 认领 引用 被引量：23
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作者 李燕 冯博琴 鲁晓锋 《计算机工程》 CAS 北大核心 2009年第22期44-46,49,共3页
数据预处理是Web日志挖掘中的重要步骤,一般分为数据清理、用户识别、会话识别和路径补充。为消除代理服务器、防火墙和本地缓存对Web日志带来的影响,采用基于引用的分析方法完成用户会话识别和路径补充。实验结果表明,在Web访问日志中... 数据预处理是Web日志挖掘中的重要步骤,一般分为数据清理、用户识别、会话识别和路径补充。为消除代理服务器、防火墙和本地缓存对Web日志带来的影响,采用基于引用的分析方法完成用户会话识别和路径补充。实验结果表明,在Web访问日志中的记录引用信息较完整的情况下,该方法可以高效地获得用户的访问路径。 展开更多
关键词 Web日志挖掘 数据预处理 用户会话识别 路径补充
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基于Web日志的用户访问路径提取与分析 认领 引用 被引量：8
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作者 刘颖 彭赓 +2 位作者 吕本富 陈杰 梅梅 《情报学报》 CSSCI 北大核心 2009年第4期548-556,共9页
线上购物相对线下购物的一个特点是可以将用户的购物过程记录到网站的Web日志中,为研究用户网上行为特征提供必要的数据支持。本文详细介绍了对Web日志数据进行预处理的一系列步骤和方法,并以某出版社网站18天的日志数据为实证,提取出... 线上购物相对线下购物的一个特点是可以将用户的购物过程记录到网站的Web日志中,为研究用户网上行为特征提供必要的数据支持。本文详细介绍了对Web日志数据进行预处理的一系列步骤和方法,并以某出版社网站18天的日志数据为实证,提取出用户的访问路径（访问页面的先后次序）,分析路径信息得到用户在不同页面之间访问的转换概率,从而定量地衡量购物流程中各步骤之间的转换率和贡献率,提炼出用户最有可能的前向转换路径和后向转换路径,以期对网站流程优化和商品促销设置提供决策支持。 展开更多
关键词 Web日志 数据预处理 访问路径 转换概率
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