Data transmission protocol identification and analysis method for a power transmission system

Abstract

The invention relates to the technical field of power transmission systems, in particular to a data transmission protocol identification and analysis method for a power transmission system, which comprises the following steps of: step S101, analyzing network packet data into session data; step S102, judging whether the entity part of the session data conforms to a preset data format or not; step S103, performing multi-mode matching on the session data meeting the preset data format; and S104, labeling according to the data format of the session data and the hit position of the preset feature string. After the method is adopted, the process is simple. According to the invention, the analyzed session data is judged in the preset data format; Compared with the prior art, the method has the advantages that invalid data which do not conform to the preset data format can be filtered out, the data extraction time is shortened, in addition, by conducting multi-mode matching on the session datawhich conform to the preset data format, the searching and matching time in the data extraction process is further shortened, and the full-text data extraction efficiency of mass data is improved.

Description

technical field [0001] The invention relates to the technical field of power transmission systems, in particular to a method for identifying and analyzing data transmission protocols used in power transmission systems. Background technique [0002] With the rapid development of the Internet, data has penetrated into every industry and business function field, and has gradually become an important factor of production, accompanied by massive data that humans can analyze and process. In medium-sized and above cities such as Beijing and Shanghai, various types of data generated in network activities every day have exceeded PB level. For example, mobile phone applications will generate several terabytes of submitted data every day. These data contain information such as latitude and longitude, mobile phone serial number, user identification card number, mobile phone unique identification code, etc., and these information are very useful in the security supervision industry. Inf...

AI Technical Summary

Problems solved by technology

For example, mobile phone applications will generate several terabytes of submitted data every day. These data contain information such as latitude and longitude, mobile phone serial number, user identification card number, mobile phone unique identification code, etc., and these information are very useful in the security supervision industry. Information becomes an important and complex job

[0003] There are two traditional full-text extraction methods: one is the template-based extraction method, which is suitable for the information extraction of a specific website, but it is powerless for the data generated by the changeable mobile APP and different websites; One is to extract full-text content based on regular expressions. This method is suitable for offline full-text extraction with a small amount of data. Once faced with a large amount of data submitted by APP, the efficiency is relatively low.

Therefore, in the case of a large amount of data, these two methods will consume a lot of manpower, and the efficiency is low, and they can no longer meet the needs in the case of a large amount of data.

Images