Research On Intrusion Detection Model Based On Cost-Sensitive

With the rapid development of modern technology, the style of work and life has been greatly changed compared with the traditional way so that the application of computer network has become essential for us. Computer system plays an important role in different area of society, while it also brings severe security problem with the development of the high-speed Internet connection. User's computer, user's information source and the commercial secret have become the objects of the lawless attack, which has troubled us seriously now. To solve the security problem, a series of security architecture, security model and security system have been explored.There is a sophisticated and data's great capacity tread with the progress of current network application, computer architectureand intrusion detection technology. In the current IDS, some problems should be solved about the cost efficiency to meet the need for the detection of real time system.Intrusion detection system must maximize the realization of security goals while minimizing costs.In this paper, we study the problem of building cost-sensitive intrusion detection models. We examine the major cost factors associated with an IDS, which include development cost, operational cost, damage cost due to successful intrusion, and the cost of manual and automated response to intrusion. These cost factors can be qualified according to a defined attack taxonomy and site-specific security policies and priorities.We define cost models to formulate the total expected cost of an IDS. We present cost-sensitive machine learning techniques that can produce detection models that are optimized for user-defined cost metrics. We mainly researches the cost factors based on the host and defines the relative values so that the cost-sensitive modeling algorithm can be introduced to the Intrusion Detection field based on the host. According to specialresource limited condition of Intrusion Detection field based on the host;dynamic detection method which can detect using different sets of rules has been put forward considering computing resource of host system.Empirical experiments show that our cost-sensitive modeling and deployment techniques are effective in reductive in reducing the overall cost of intrusion detection.