網(wǎng)站異常變化監(jiān)測(cè)系統(tǒng)的研究與實(shí)現(xiàn)
[Abstract]:With the development of Internet technology and the arrival of big data era, website has become a platform for government agencies, enterprises and institutions, cultural media, scientific research institutions, financial and securities institutions and other information dissemination and comprehensive application platform. The usage of websites is increasing year by year, and the content of web pages is huge and complicated. It is the responsibility of website owners to ensure the security, authority and accuracy of website information and to provide correct information and services for the public. However, the security threats to websites are becoming more and more serious, and the behavior of illegal intrusion and tampering is emerging in endlessly. The real-time monitoring and tamper-proof technology of websites has become a hot research topic in the field of information security. The design and development of a system to monitor the abnormal changes of websites is of great significance to the security of websites. In this paper, a set of abnormal change monitoring system is proposed to solve this problem. Firstly, this paper studies the characteristics of the abnormal changes of web pages, inquires the principles and techniques of the software of various kinds of website content security system, and finally selects the monitoring system of the abnormal changes of the website based on Hadoop platform through the comprehensive comparison and research of the advantages and disadvantages. The main functions expected to be realized in this system include the acquisition of website file data, abnormal change detection and monitoring and alarm. These include crawling a large number of complete website file data, storing the file data by HDFS, and carrying out preliminary filtering, and then detecting the specific changing content of the website, as well as the legitimacy judgment of the change, the management of abnormal data, and so on. Using the distributed computing model of HDFS and MapReduce, a file management system provided by Hadoop platform is used to deal with a large number of web site file data. The system carries on the HDFS storage to a large number of website file data which crawls, and speeds up the data search through the index storage way. The MD5 information digest algorithm and the improved text comparison algorithm based on graph theory are used to detect the abnormal change in the system, and the MapReduce computing model is used to realize the fast and accurate anomaly change detection. To judge the illegal link, URL address is translated into IP address, matching filter is used to judge the illegal word, Chinese word segmentation technology is combined with naive Bayes classification algorithm in data mining, and abnormal information is filtered out. Through the system design, implementation and testing, the system basically meets the requirements of monitoring the abnormal changes of the website in function and performance. The system also shows stable, efficient and error-free operation in use.
【學(xué)位授予單位】:遼寧大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:TP393.092
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