• cpe
• cve
• filtering
• information retrieval
• matching

The identification and matching of Common Platform Enumerations (CPEs) play a critical role in accurately filtering the vulnerabilities described by Common Vulnerabilities and Exposures (CVEs). This study evaluates various matching techniques, focusing on their applicability to structured data such as CPE fields. It investigates approaches to enhance match accuracy by exploiting the structured nature of CPEs and incorporating additional metadata to deal with unstructured and noisy inputs. The research also addresses challenges in balancing accuracy and usability, proposing methods to optimize the trade-offs between automation and manual intervention. These findings aim to inform the design and implementation of an effective and adaptable algorithm for personalized CVE filtering.