论文标题
应用于网络安全异常检测问题的贝叶斯模型
Bayesian Models Applied to Cyber Security Anomaly Detection Problems
论文作者
论文摘要
网络安全是全球所有个人，组织和政府的重要问题。网络攻击变得比以往任何时候都变得更加复杂，频繁和危险，并且在处理这些新类别的网络威胁时，传统的异常检测方法被证明效果不佳。为了解决这个问题，古典和贝叶斯模型都提供了传统基于签名方法的有效且创新的替代方案，激发了人们对统计研究的日益兴趣，近年来已经观察到了它。在这篇评论中，我们提供了一些典型的网络安全挑战，典型的数据和统计方法的描述，并特别注意针对这些问题的贝叶斯方法。
Cyber security is an important concern for all individuals, organisations and governments globally. Cyber attacks have become more sophisticated, frequent and dangerous than ever, and traditional anomaly detection methods have been proved to be less effective when dealing with these new classes of cyber threats. In order to address this, both classical and Bayesian models offer a valid and innovative alternative to the traditional signature-based methods, motivating the increasing interest in statistical research that it has been observed in recent years. In this review we provide a description of some typical cyber security challenges, typical types of data and statistical methods, paying special attention to Bayesian approaches for these problems.
