Towards Improving E-mail Content Classification for Spam Control: Architecture, Abstraction, and Strategies

This dissertation discusses techniques to improve the effectiveness and the efficiency of spam control. Specifically, layer-3 e-mail content classification is proposed to allow e-mail pre-classification (for fast spam detection at receiving e-mail servers) and to allow distributed processing at network nodes for fast spam detection at spam control points, e.g., at e-mail servers. Fast spam detection allows prioritizing e-mail servicing at receiving e-mail servers to safeguard non-spam e-mail deliveries even under heavy spam traffic. Fast spam detection also allows spam rejection during Simple Mail Transfer Protocol sessions for inbound and outbound spam control. We have four contributions in the dissertation. In our first contribution, we propose a hardware architecture for näıve Bayes content classification unit for a high-throughput spam detection computation. We