【作者】 郭江鸿；

【导师】 吴良杰；

【作者基本信息】 哈尔滨工程大学 ， 计算机应用技术， 2007， 硕士

【摘要】 随着Internet的迅速发展和普及，电子邮件以其方便、快捷、成本低等特点而成为人们生活中重要的通信手段之一。但随之而生的垃圾邮件，则占用了大量网络资源，浪费了网民的宝贵时间，造成了巨大的经济损失。因此，研究和设计一种能够高效过滤垃圾邮件的电子邮件系统，有着重大的现实意义。人工免疫系统是一门新兴的科研领域，它提取、发现和应用生物免疫系统的有效机制来解决工程和科学问题。本课题的研究目的就是要利用人工免疫系统机制设计一个对垃圾邮件具有免疫能力的电子邮件系统，为这一领域的应用探索一条有效的途径。论文在综合分析传统反垃圾邮件技术的原理、优势和不足的基础上，对生物免疫机制及其在计算机领域的应用和算法作了深入研究，提出了构建免疫电子邮件系统的新设想，该系统具有对外界环境动态自适应以及能够及时识别新特征邮件等优良特性，这恰好弥补了传统技术这方面的不足。论文的创新点在于提出并设计了一个免疫电子邮件系统模型，该模型针对邮件系统的特点定义了抗原抗体编码、设计和改进了亲和力计算方法，将诸多免疫机制应用到模型中来，为充分体现自学习、记忆、自适应、多样性等良好免疫特性，模型分别设计了有效的解决方案。其中对克隆选择算法进行重点改进，保证了抗体的多样性。论文最后针对免疫电子邮件模型进行了仿真试验，对比了算法改进前后的实验结果，改进后算法使系统召回率有了一定程度的提高，同时虚报率也有所下降，证明了算法改进的有效性以及免疫电子邮件系统模型的适用和合理性。更多还原

【Abstract】 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.更多还原