CAN模糊测试软件数据集

本数据集基于系统化的CAN模糊测试方法，采集和分析异常报文、攻击数据及车辆响应情况，为车载ECU安全防护、异常检测模型训练及汽车网络安全评估提供可靠的数据支持。通过该数据集，研究人员和安全工程师可以深入探索CAN总线的潜在安全漏洞，并优化车联网的防御策略。数据集共包括三个数据文件夹，其中：（1）存放测试过程中采集的原始CAN报文数据，包括 时间戳、CAN ID、数据段 等信息。以 CSV、JSON 或二进制日志格式 存储，便于解析和后续分析，数据量378MB。（2）包含 目录遍历、数据变异、重放攻击、DoS攻击、泛洪攻击 生成的异常报文。记录攻击类型、攻击参数、异常触发情况，用于分析车辆对不同攻击的响应，数据量372MB。（3）存放 数据统计、异常报文检测结果、车辆响应分析 等报告。包括 可视化图表、日志比对分析、攻击影响评估 等，便于进一步研究和优化防御策略，数据量40.1KB。This dataset is developed based on a systematic CAN fuzz testing methodology, which collects and analyzes abnormal CAN messages, attack data and vehicle response scenarios, providing reliable data support for in-vehicle ECU security protection, anomaly detection model training and automotive cybersecurity evaluation. Through this dataset, researchers and security engineers can thoroughly explore potential security vulnerabilities of the CAN bus, and optimize the defense strategies for the Internet of Vehicles. The dataset includes three data folders: 1. Stores the original CAN message data collected during the test, including information such as timestamps, CAN IDs, data segments and more. It is stored in CSV, JSON or binary log formats to facilitate parsing and subsequent analysis, with a total data volume of 378 MB. 2. Contains abnormal messages generated by directory traversal attacks, data mutation attacks, replay attacks, DoS attacks and flood attacks. It records attack types, attack parameters and abnormal trigger conditions, which are used to analyze vehicle responses to different attacks, with a total data volume of 372 MB. 3. Stores reports such as data statistics, abnormal message detection results and vehicle response analysis, including visual charts, log comparison analysis, attack impact assessment and more, which facilitate further research and defense strategy optimization, with a total data volume of 40.1 KB.

搜集汇总

背景与挑战

背景概述

该数据集基于系统化的CAN模糊测试方法构建，包含原始CAN报文、多种攻击生成的异常报文及相关分析报告，旨在为车载ECU安全防护、异常检测模型训练及汽车网络安全评估提供数据支持。通过该数据集，研究人员和安全工程师可深入探索CAN总线的潜在安全漏洞，并优化车联网的防御策略。