态势感知与安全管理系统AI模型实验webshell数据集

webshell是网络安全中攻击者利用漏洞等手段实现在用户系统中注入的执行命令并获取返回结果的恶意文件。使用AI模型检测webshell是一种高效的安全检测手段。态势感知与安全管理系统AI模型实验webshell数据集是基于数据采集模块，收集网络上公开的和课题模拟的webshell攻击样本，并使用已知的webshell攻击进行重放抓取pcap包生成的文件。其主要记录了ip，端口，流量大小等观测值，数据量3万于条。它是webshell攻击检测模型创建过程中的中间产物，为后续基于算子算法奠定了数据基础，根据此数据和算子算法共同进行AI训练，产生最后的webshell的AI检测模型，并可以用于检测其他的可疑pcap包。该模型可以帮助态势感知与安全管理系统对于明显具体webshell特征的数据进行及时的告警处置，有效保护网络协同制造平台的安全工作环境。数据集大小为8.15MB。

A webshell is a malicious file that enables attackers to execute commands and retrieve corresponding results by exploiting vulnerabilities or other means to inject it into a user's system in the field of cybersecurity. Detecting webshells using AI models is an efficient security detection approach. The Webshell Dataset for AI Model Experiments of the Situation Awareness and Security Management System is generated via a data collection module, which collects publicly available and project-simulated webshell attack samples from the network, and captures pcap files by replaying known webshell attacks. This dataset mainly records observation metrics including IP addresses, ports, traffic volume and others, with a total of over 30,000 entries. As an intermediate product in the development of webshell attack detection models, this dataset lays a data foundation for subsequent operator-based algorithms. AI training is conducted using this dataset and operator algorithms to produce the final webshell AI detection model, which can be used to detect other suspicious pcap files. This model can help the Situation Awareness and Security Management System perform timely alerting and handling for data with distinct webshell-specific characteristics, effectively safeguarding the secure working environment of network collaborative manufacturing platforms. The total size of this dataset is 8.15 MB.

搜集汇总

背景与挑战

背景概述

该数据集是针对webshell攻击检测的AI模型实验数据，包含3万余条记录，主要记录了IP、端口、流量大小等观测值，数据量为8.15MB。数据集用于训练AI模型，以检测具有webshell特征的网络流量，提升网络安全防护能力。