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Realizing a Sub-Linear Time String-Matching Algorithm With a Hardware Accelerator Using Bloom Filters

机译:使用布隆滤波器的硬件加速器实现亚线性时间字符串匹配算法

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摘要

Many network security applications rely on string matching to detect intrusions, viruses, spam, and so on. Since software implementation may not keep pace with the high-speed demand, turning to hardware-based solutions becomes promising. This work presents an innovative architecture to realize string matching in sub-linear time based on algorithmic heuristics, which come from parallel queries to a set of space-efficient Bloom filters. The algorithm allows skipping characters not in a match in the text, and in turn simultaneously inspect multiple characters in effect. The techniques to reduce the impact of certain bad situations on performance are also proposed: the bad-block heuristic, a linear worst-case time method and a non-blocking interface to hand over the verification job to a verification module. This architecture is simulated with both behavior simulation in C and timing simulation in HDL for antivirus applications. The simulation shows that the throughput of scanning Windows executable files for more than 10000 virus signatures can achieve 5.64 Gb/s, while the worst-case performance is 1.2 Gb/s if the signatures are properly specified.
机译:许多网络安全应用程序都依靠字符串匹配来检测入侵,病毒,垃圾邮件等。由于软件实现可能无法跟上高速需求,因此转向基于硬件的解决方案变得很有希望。这项工作提出了一种创新的体系结构,可以基于算法启发式在亚线性时间内实现字符串匹配,该算法从并行查询到一组节省空间的Bloom过滤器。该算法允许跳过文本中不匹配的字符,并依次检查有效的多个字符。还提出了减少某些不良情况对性能的影响的技术:不良块启发法,线性最坏情况时间方法和无阻塞接口以将验证工作移交给验证模块。针对防病毒应用程序,使用C中的行为仿真和HDL中的时序仿真对这种体系结构进行了仿真。仿真显示,扫描Windows可执行文件以获取10000多个病毒签名的吞吐量可以达到5.64 Gb / s,而如果正确指定了签名,则最坏情况下的性能为1.2 Gb / s。

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