Bayesian Models Applied to Cyber Security Anomaly Detection Problems

Abstract

Summary 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.

The Exigency for Resilient and Cyber-Secure Critical Infrastructure in the Caribbean

“…Making Bayesian methods attractive for incorporating them in anomaly detection frameworks as the uncertainty can be propagated to predictions resulting in them being more stable. Bayesian models also allow the combination of different types of information in a single framework which allows for a general form for reasoning known as Bayesian reasoning (Perusquía et al, 2022).…”