Study On Key Technology And Algorithm Of Immune Email System

With the rapid development and popularity of Internet, e-mail becomes an important means of communication in people's lives because of its convenient, fast, low cost features. But spam emails use a lot of network resources, waste valuable time of Internet users, cause enormous economic losses. Therefore, study and design of a high-efficiency filter for a spam e-mail system are of great practical significance.Artificial Immune System is an emerging field of scientific research. It can extract discovery and apply an effective mechanism of a biological immune system to solve engineering and scientific problems. The purpose of the thesis is designing an email system which can be immune to spam emails by using artificial immune system mechanisms, and exploring an effective way for the application in this area.In this thesis biological immunological mechanisms, computer field applications and algorithms are in-depth studied on the basis of a comprehensive analysis of traditional anti-spam technique theories, strengths and weaknesses. A new immune e-mail system is proposed. The system have excellent characteristics such as dynamic adaptive to an external environment and timely identification new mail features, which is a remedy for traditional deficiency.The innovation in this thesis is that an e-mail immune system model is proposed and designed. The model definite antigen-antibody codes according to mail system characteristics, and design and improve affinity calculation method. Many immune mechanisms are applied to the model. In order to fully reflect good characteristics such as learning, memory, adaptive and immune diversity, effective solutions are designed in this model. Clone selection algorithm is improved to ensure the antibody diversity.Finally, in this thesis a simulation test is made for immune e-mail system model. The experimental results between before improving and after improving are compared. The improved algorithms make the system recall rate increased and false rate decreased. So it can proof the improved algorithm effectiveness and application and reasonability of the immune e-mail system model.