Machine Learning and Data Analytics for Cyber Security

Abstract

The aim of this reprint is to provide an overview of the current challenges within the cyber security community today, as recognized by our contributors. This reprint provides 16 papers from the Topical Collection on “Machine Learning and Data Analytics for Cyber Security” that cover topics of large language models for cybersecurity claim classification, adversarial machine learning attacks against intrusion detection systems, the detection of PLC process control anomalies, identifying session-replay bots compared to human users, and mitigating against side-channel attacks.