Cybert CyNER
A cybersecurity entity recognition model fine-tuned on the CyNER dataset based on CYBERT, used to identify named entities related to cyber threats.
Downloads 31
Release Time : 12/6/2023
Model Overview
This model is specifically designed for the cybersecurity field as a Named Entity Recognition (NER) model, capable of identifying threat-related entities in text, such as attackers, vulnerabilities, malware, etc.
Model Features
Cybersecurity Specialization
Entity recognition capabilities optimized specifically for cybersecurity domain texts
High Accuracy
Achieves 95.68% accuracy on the evaluation set
Fine-grained Entity Recognition
Capable of identifying multiple types of cybersecurity-related entities
Model Capabilities
Cybersecurity Text Analysis
Threat Intelligence Extraction
Security Incident Report Processing
Use Cases
Security Operations
Threat Intelligence Analysis
Automatically extracts key threat entities from security reports
Improves analysts' efficiency in processing threat intelligence
Security Incident Report Processing
Automatically identifies key elements in security incident reports
Accelerates incident response processes
Security Research
Vulnerability Research
Extracts vulnerability-related information from technical documents
Assists researchers in quickly locating key information
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