Modeling Sparse and Bursty Vulnerability Sightings
This paper presents a novel statistical framework for modeling the sparse and bursty nature of vulnerability sightings in real-world data. The approach captures the temporal patterns of vulnerability discoveries, which often occur in clusters rather than uniformly over time, providing better predictive capabilities for cybersecurity risk assessment.