Comprehensive Vehicular Communication Network Attack Dataset

Abstract: This dataset captures critical vehicular-specific attacks (Position Spoofing, Sybil, and Wormhole) in Vehicular Communication Networks (VCNs). It incorporates legitimate and malicious instances generated using realistic mobility patterns, positional dynamics, and temporal interactions.

Dataset Details:

Instances:

Spoofing: 45,975 legitimate, 589 malicious

Wormhole: 52,237 legitimate, 5,219 malicious

Sybil: 14,829 legitimate, 1,753 malicious

Features Included: Mobility dynamics (speed, rate of distance change), Positional features (location, inter-vehicle distances), Temporal features (time intervals), Communication metrics (packets count, transmission rates, reception rates, hop counts), Attack-specific labels (Spoofing, Sybil, Wormhole)

摘要：本数据集收录了车载通信网络（Vehicular Communication Networks，VCNs）中三类关键的车载专属攻击：位置欺骗（Position Spoofing）、Sybil攻击（Sybil）以及虫洞攻击（Wormhole）。数据集涵盖了基于真实移动模式、位置动态特性与时空交互生成的合法与恶意样本。

数据集详情：
样本分布：
位置欺骗攻击：合法样本45,975条，恶意样本589条
虫洞攻击：合法样本52,237条，恶意样本5,219条
Sybil攻击：合法样本14,829条，恶意样本1,753条
包含特征：移动动态特征（行驶速度、距离变化率）、位置特征（车辆位置、车间距离）、时空特征（时间间隔）、通信指标（数据包数量、传输速率、接收速率、跳数）以及攻击专属标签（位置欺骗、Sybil、虫洞）