更智能地搜索网络数据包数据库

W. Kenworthy
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引用次数: 0

摘要

生物信息学已经开发出一些非常复杂的算法,用于在测序项目产生的大量数据中进行搜索。这里介绍的是一种方法,它利用这些算法来处理计算机网络数据流量,以一种避免处理网络数据包的更传统方法所需的许多操作的方式来查找和分类信息。可以使用它来避免通过协议栈处理数据,以便提取内容以使其为搜索做好准备,并且能够访问为生物数据开发的高级搜索功能。可以在结构签名数据库中直接搜索原始数据(例如整个以太网数据包或字符串/图案),以通过查询数据包中的结构指示感兴趣的数据包。这里提到的结构是数据中的“模式的模式”。本文描述了基于生物信息学技术创建可检索数据库并使用样本数据进行检索所获得的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smarter searching for a network packet database
Bioinformatics has developed some very sophisticated algorithms used for searching within the large amounts of data produced by sequencing projects. Introduced here is a method that leverages these algorithms for processing computer network data traffic to find and classify information in a way that avoids many of the operations that are required of more traditional methods of processing network data packets. It can be used to avoid processing the data through a protocol stack in order to extract the content to make it ready for searching as well as being able to a access the advanced search capabilities developed for biological data. Raw data (for example whole Ethernet packets or strings/ motifs) can be directly searched for within a database of structure signatures to indicate packets of interest via structures within the query packet. The structures referred to here are the “patterns of patterns” within the data. This paper describes the results obtained by creating a searchable database based on bioinformatics techniques and searching it using sample data.
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