A Behavior-Based Anti-Spam Technology Based on Immune-Inspired Clustering Algorithm

The paper describes a novel behavior-based anti-Spam technology at email service based on an immune-inspired clustering algorithm. Compared with popular client anti-Spam filtering system based on content classification technology, our approach is capable of continuously delivering the most relevant Spam from the collection of all Spam that is reported by members of the network., then mail servers shall implement anti-Spam technology by using the “Black lists” that have been recognized. Experiment are discussed with real-world datasets, the conclusion have shown the technology is reliable, efficient and scalable, because no single technology can achieve one hundred percent Spam detection with zero false positives, however, it can be used in conjunction with other filtering systems to minimize errors.