针对目前垃圾邮件制造者不断利用新技术和新方法,使垃圾邮件的内容和发送手段等都发生了很大的变化,对传统基于内容的邮件检测技术提出了严峻挑战。本论文根据人工免疫的工作原理,采用阴性选择算法,提出了一种主动的,具有自组织、自学习、自适应等特点的垃圾邮件检测模型。实验结果表明,该模型可以有效识别与拦截垃圾邮件,提高了垃圾邮件检测效率和准确率。 In response to the continuous use of new technologies and new methods by spammers, spam content and sending methods have undergone tremendous changes, posing a serious challenge to traditional content-based email detection technologies. According to the working principle of artificial immune and negative selection algorithm, this paper proposes a kind of active spam detection model with self-organization, self-learning and self-adapting. Experimental results show that this model can effectively identify and block spam and improve the efficiency and accuracy of spam detection.