A Scalable Spam Filtering Architecture

Abstract

Abstract. The proposed spam filtering architecture for MTA 1 servers is a component based architecture that allows distributed processing and centralized knowledge. This architecture allows heterogeneous systems to coexist and benefit from a centralized knowledge source and filtering rules. MTA servers in the infrastructure contribute to a common knowledge, allowing for a more rational resource usage. The architecture is fully scalable, ranging from all-inone system with minimal components instances, to multiple components instances distributed across multiple systems. Filtering rules can be implemented as independent modules that can be added, removed or modified without impact on MTA servers operation. A proof-of-concept solution was developed. Most of spam is filtered due to a grey-listing effect from the architecture itself. Using simple filters as Domain Name System black and white lists, and Sender Policy Framework validation, it is possible to guarantee a spam filtering effective, efficient and virtually without false positives.