2021/12/02 by Inês Macedo, Macedo, Inês, Sinan Wanous +7
Computer Science · #Anomaly Detection Techniques and Applications #Cryptography and Security (cs.CR) #Data Visualization and Analytics #FOS: Computer and information sciences #Network Security and Intrusion Detection
paper · pdf · doi:10.48550/arxiv.2112.01103
openalex publication_date 2021/12/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Investigating efficiently the data collected from a system's activity can help to detect malicious attempts and better understand the context behind past incident occurrences. Nowadays, several solutions can be used to monitor system activities to detect probable abnormalities and malfunctions. However, most of these systems overwhelm their users with vast amounts of information, making it harder for them to perceive incident occurrences and their context. Our approach combines a dynamic and intuitive user interface with Machine Learning forecasts to provide an intelligent investigation tool that facilitates the security operator's work. Our system can also act as an enhanced and fully automated decision support mechanism that provides suggestions about possible incident occurrences.