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A boolean model for spam detection

Spam, also known as unsolicited or junk mail quickly became a major problem on the Internet. To address this growing burden of this type of spam, several detection techniques exist to automatically classify incoming emails as spam or legitimate. In this context, we propose a supervised classification approach based on Boolean cellular automaton. To evaluate the performance of this new approach, we conduct a series of experiments on the LingSpam corpus.