Accelerated spam filtering with enhanced KMP algorithm on GPU

Venkata Krishna Pavan Kalubandi, M. Varalakshmi
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引用次数: 2

Abstract

Spam filtering is one of the most important applications in email services that has become increasingly sophisticated due to the enormous usage of Internet. Traditionally, spam filters have been implemented on the CPU with a pattern matching algorithm. In this paper, an accelerated spam filtering mechanism that uses GPUs is presented. The filtering process utilizes an enhanced version of Knuth Morris Pratt pattern matching algorithm that outperforms the serial versions up to 12x and also performs more efficiently compared to other parallel versions. The parallel algorithm is to develop and advanced keyword based Naïve Bayesian classifier speeds up the spam filtering up to 2 times compared to CPU.
在GPU上使用增强KMP算法加速垃圾邮件过滤
垃圾邮件过滤是电子邮件服务中最重要的应用之一,由于互联网的大量使用,电子邮件服务变得越来越复杂。传统上,垃圾邮件过滤器是通过模式匹配算法在CPU上实现的。本文提出了一种基于gpu的加速垃圾邮件过滤机制。过滤过程采用增强版的Knuth Morris Pratt模式匹配算法,优于串行版本高达12倍,并且与其他并行版本相比执行效率更高。并行算法是开发一种先进的基于Naïve关键字的贝叶斯分类器,将垃圾邮件过滤速度提高到CPU的2倍。
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