数据分类方法、装置、存储介质及计算机设备

By automatically linking to the source URL in the honeypot to obtain source data and matching it with historical data, the problem of low efficiency and low accuracy caused by the large memory consumption of embedded code in the honeypot is solved, and efficient and stable data classification and analysis are achieved.

CN116545718BActive Publication Date: 2026-07-17SHANGHAI GUAN AN INFORMATION TECH

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SHANGHAI GUAN AN INFORMATION TECH
Filing Date
2023-05-17
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

The data acquisition code embedded in the honeypot consumes a lot of memory, resulting in low data acquisition efficiency and low classification accuracy for attackers. It is also prone to conflicts with the honeypot's running code, leading to abnormal data acquisition.

Method used

By responding to attack signals, the system automatically links to the source tracing URL to obtain the attacker's current source tracing data and matches it with historical source tracing data. The source tracing URL is used to avoid conflicts with the honeypot and to achieve data classification.

Benefits of technology

It improves the efficiency and accuracy of attacker attribution data acquisition, ensures stable operation of honeypots, achieves efficient data classification and classification accuracy, and supports attacker big data analysis.

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Abstract

本发明公开了一种数据分类方法、装置、存储介质及计算机设备,涉及网络安全技术领域,主要在于能够提高数据的分类效率和分类准确度。其中方法包括:响应于针对目标蜜罐的攻击信号,确定所述目标蜜罐对应的溯源网址;响应于所述溯源网址的触发指令,获取访问所述目标蜜罐的当前攻击端的当前溯源数据;确定访问所述目标蜜罐的历史攻击端的历史溯源数据,并将所述当前溯源数据与所述历史溯源数据进行匹配,得到匹配结果;根据所述匹配结果,对所述当前溯源数据进行分类,得到所述当前溯源数据对应的分类结果。本发明适用于对攻击数据进行分类。
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