Use of web Mining in Network Security
Rimmy Chuchra, Bharti Mehta, Sumandeep Kaur, Sri Sai · 2013
Abstract--Web mining is basically knowledge discovery from the World Wide Web (WWW).This practical application of data mining helps to integrate the data gathered by the traditional data mining methodologies or data mining techniques as well as data gathered by the WWW. The term Web mining has been used in three distinct ways which are web content mining, web usage mining and web structure mining. Here, we are uses Web structure mining, it is the process of using graph theory to analyze the node and connection structure of a web site. In this research paper we are uses the distinct type of web mining called “Web Structure Mining ” which helps to extract patterns from hyperlinks in a web where the function of hyperlink to connect a web page with any other location of the same or different web page. A specific hyperlink behaves like a structural component in case of “web structure mining”. In this research paper, we are merging the concept of web mining with the network security so that we can easily detect the online attacks occur on the network by using web agents (i.e.- web agents are basically web robots) rather than using man power effort. The major objective is to reduce cost as well as time while identifying online attack. Here we use “rule induction data mining technique ” to achieve maximum accuracy of results. The special focus is to detect online active attack by the web agents after that they will provide security by using various mechanisms and techniques. In this way, we can also say that these web agents help to protect us from attacker during online data transfer which follows the concept of network security. The first task of web agents is to identify the type of active attack after that provide several ways to prevent security. In this way we can use a “Hybrid approach” (i.e.- web mining with network security).The major benefit to use this hybrid approach is to save time and cost which are the major objectives of data mining.