Hybrid Spam Filtering for Mobile Communication

TL;DR

This paper proposes a hybrid spam filtering framework for mobile communication that combines content-based filtering and challenge-response techniques, balancing accuracy and communication overhead based on spam prevalence.

Contribution

It introduces a novel hybrid anti-spam framework that optimally combines content filtering and challenge-response, addressing limitations of individual methods.

Findings

Filtering parameters should be adjusted based on spam message proportion.

Hybrid approach improves spam detection accuracy.

Trade-offs exist between filtering accuracy and communication overhead.

Abstract

Spam messages are an increasing threat to mobile communication. Several mitigation techniques have been proposed, including white and black listing, challenge-response and content-based filtering. However, none are perfect and it makes sense to use a combination rather than just one. We propose an anti-spam framework based on the hybrid of content-based filtering and challenge-response. There is the trade-offs between accuracy of anti-spam classifiers and the communication overhead. Experimental results show how, depending on the proportion of spam messages, different filtering %%@ parameters should be set.