|
In recent years, with the more complex change of the domestic and foreign environment, various hostile forces infiltrated gradually by the campus net, the state take more strictly to the monitor of network information and more rapidly to the response of sensitive information, The Ministry of Public Security, the Ministry of Network Supervision and the Education Department have taken campus network information security as one of the key work of campus safety, which they demand the various units to paid more attention to universities information security management, Just like high tension line that cannot touch. Therefore, the study of Web sensitive information filtering of college digital campus has important practical significance.At present, numerous IT technology manufacturers have developed information safety monitoring system for Internet, which is advanced, function is various and powerful, but the targeted isn’t clear,, and the operating is complex and deploy up, they must match the hardware equipment which manufacturer designated and the price does not poor. They mostly aim at intercepting the network layer of the network packets, intercept HTTP’s response data report, and then analyze the HTTP data report, and after filtering the first layer packets IP address, and then to filter the content. The products of IT companies developed on the basis of web general situation is general, which means more function, filtering comparatively, But actually, campus network application service usually are mainly active service, data source relatively simple, too much function, filtering comparatively would cause overall user experience declining and function couldn’t use properly. Meanwhile university scientific research outlays are nervous and to build a conservation-minded campus is the most universities advocate the development idea. In such background, to purchase this monitoring system of manufacturers studies is unreasonable, firstly, the ratio is not reasonable, secondly,The general of monitoring system couldn’t not always appropriate or meet the specific needs of university network, which would cause the huge waste of devices and functions. From the point of view of the university information security should dominate by themselves, This paper aimed at the real situation that the college digitalization campus Web information filtering (in fact, filtering was a static text which involved with a pile of stored in the Web server, just need to get the legal and sensitive classification to this static text and then complete filtering. On the basis of the probability statistical Bayesian algorithm, it puts forward an improved filtering algorithm and designed the complete filtering model to filter Web text. This method can be filtered applied to the server or system management, and to make active filter, which can avoid the great waste of the money and the function, and hope that it can provide a reference solution for solving the problem of universities information security.This paper first elaborates the general existing situation of campus digital Web construction, and the existing problem of information security that must be solved. About involved with the Chinese word segmentation problem in filtering, this paper adopts a positive maximal matching algorithm, and according to the actual situation, the algorithm was improved, and gets the idea of participle effect. when design the filtering algorithm, this paper studies and analyzes the Bayesian algorithm, which considers if would occur risk when sensitive information intercepted which brings misjudgment, so it introduces the method of loss factor and the utilization management feedback, and proposes the highest level of security filtering algorithm which based on the Minimum Risk Bayesian decision-making, and do some research which based on the algorithm’s application to the digital campus Web text information content filtering. According to actual condition, this paper introduces the idea of buffering, so as to improve Bayesian Incremental learning algorithm, which makes classifier can better adapt to the growing mass data classification task. In addition, in order to verify the correctness of the proposed design ideas, the author adopts data sets to do the experiment in Java environment, and the result shows that this design filtering model is feasible, and to a certain extent it can improve the effect of filtering. The last phrase is this paper summary and outlook.
|