Cybersecurity Risk Management through Behavior-Based Contextual Analysis of Online Logs  

作　　者：Irawati Edlabadkar Vijay K. Madisetti Irawati Edlabadkar;Vijay K. Madisetti(School of Cybersecurity & Privacy, Georgia Institute of Technology, Atlanta, GA, USA)

机构地区：[1]School of Cybersecurity & Privacy, Georgia Institute of Technology, Atlanta, GA, USA

出　　处：《Journal of Software Engineering and Applications》2024年第6期487-507,共21页软件工程与应用（英文）

摘　　要：This paper studies cyber risk management by integrating contextual log analysis with User and Entity Behavior Analytics (UEBA). Leveraging Python scripting and PostgreSQL database management, the solution enriches log data with contextual and behavioral information from Linux system logs and semantic datasets. By incorporating Common Vulnerability Scoring System (CVSS) metrics and customized risk scoring algorithms, the system calculates Insider Threat scores to identify potential security breaches. The integration of contextual log analysis and UEBA [1] offers a proactive defense against insider threats, reducing false positives and prioritizing high-risk alerts.This paper studies cyber risk management by integrating contextual log analysis with User and Entity Behavior Analytics (UEBA). Leveraging Python scripting and PostgreSQL database management, the solution enriches log data with contextual and behavioral information from Linux system logs and semantic datasets. By incorporating Common Vulnerability Scoring System (CVSS) metrics and customized risk scoring algorithms, the system calculates Insider Threat scores to identify potential security breaches. The integration of contextual log analysis and UEBA [1] offers a proactive defense against insider threats, reducing false positives and prioritizing high-risk alerts.

关 键 词：Cyber Risk UEBA CVSS 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]