SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Data mining: concepts and techniques
Data mining: concepts and techniques
Collision Module Integration in a Specific Graphic Engine for Terrain Visualization
IV '04 Proceedings of the Information Visualisation, Eighth International Conference
Approximate object location and spam filtering on peer-to-peer systems
Proceedings of the ACM/IFIP/USENIX 2003 International Conference on Middleware
A multiagent-based peer-to-peer network in Java for distributed spam filtering
CEEMAS'03 Proceedings of the 3rd Central and Eastern European conference on Multi-agent systems
Behavior-based spam detection using a hybrid method of rule-based techniques and neural networks
Expert Systems with Applications: An International Journal
Combining neural networks and semantic feature space for email classification
Knowledge-Based Systems
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Spam (or junk email) has been a major problem on the Internet. A lot of solutions have been proposed to deal with it. However, with the evolvement of spammers' techniques and the diversification of email content, the traditional anti-spam approaches alone are no longer efficient. In this paper, a new anti-spam Peer-to-Peer (P2P) model based on immunity was presented. Self, Nonself, Antibody, Antigen and immune cells in email system were defined. The model architecture, the process of Antigen presenting, clone selection and mutation, immune tolerance, immune response, life cycle of immune cells and some other immune principles were described respectively. The analyses of theory and experiment results demonstrate that this model enjoys better adaptability and provides a new attractive solution to cope with junk emails in P2P environment.