论文标题
对网络安全的拓扑数据分析的综述
A Review of Topological Data Analysis for Cybersecurity
论文作者
论文摘要
在网络安全方面，通常只能通过结合许多妥协的弱指标来检测恶意或异常活动，而单独妥协的任何一个都可能不会引起怀疑。此类指标采取的道路也可能是关键的。这使得分析网络安全数据的问题特别适合拓扑数据分析（TDA），该领域使用代数拓扑的技术研究数据的高级别结构，包括探索性分析，也是机器学习工作流程的一部分。通过引入TDA并审查其应用于网络安全的工作，我们希望向研究人员强调一个有希望的新领域，具有强大的潜力，可以改善网络安全数据科学。
In cybersecurity it is often the case that malicious or anomalous activity can only be detected by combining many weak indicators of compromise, any one of which may not raise suspicion when taken alone. The path that such indicators take can also be critical. This makes the problem of analysing cybersecurity data particularly well suited to Topological Data Analysis (TDA), a field that studies the high level structure of data using techniques from algebraic topology, both for exploratory analysis and as part of a machine learning workflow. By introducing TDA and reviewing the work done on its application to cybersecurity, we hope to highlight to researchers a promising new area with strong potential to improve cybersecurity data science.
