Compression‐based spam filter
Tiago A. Almeida, Akebo Yamakami · Security and Communication Networks · 2012
Abstract Nowadays, e‐mail spam is not a novelty, but it is still an important problem with a high impact on the economy. Spam filtering poses a special problem in text categorization, in which the defining characteristic is that filters face an active adversary, which constantly attempts to evade filtering. In this paper, we present a novel approach to spam filtering based on a compression‐based model. We have conducted an empirical experiment on eight public and real non‐encoded datasets. The results indicate that the proposed filter is fast to construct, is incrementally updateable, and clearly outperforms established spam classifiers. Copyright © 2012 John Wiley & Sons, Ltd.