不可能旅行数据集

不可能旅行数据集是由北卡罗来纳大学威尔明顿分校创建的，包含73条真实和虚假的入侵检测系统（IDS）警报，源自实际的不可能旅行场景。数据集内容包括认证城市、成功登录次数、失败登录次数、源提供商等信息，通过添加随机噪声基于真实样本生成。数据集旨在通过模拟IDS警报，研究IDS虚假警报率对分析师正确分类警报能力的影响，从而评估数据集质量并改进网络安全分析工具的性能。

The Impossible Travel Dataset was created by the University of North Carolina Wilmington. It contains 73 real and false Intrusion Detection System (IDS) alerts derived from actual impossible travel scenarios. The dataset includes information such as authenticated cities, successful login counts, failed login counts, source providers and other related details, and is generated from real samples with added random noise. This dataset is designed to simulate IDS alerts to study the impact of IDS false alarm rates on analysts' ability to correctly classify alerts, so as to evaluate dataset quality and improve the performance of cybersecurity analysis tools.