Distilbert Network Intrusion Detection
A network intrusion detection model optimized based on the DistilBERT architecture, used to identify and analyze anomalous behaviors in network traffic
Downloads 165
Release Time : 2/2/2025
Model Overview
This model is a fine-tuned version of DistilBERT, specifically designed for network intrusion detection tasks, capable of analyzing network traffic data and identifying potential security threats
Model Features
Lightweight Architecture
Based on the DistilBERT architecture, it is more lightweight than standard BERT models while maintaining high performance
Cybersecurity Analysis
Specially optimized for network traffic data, capable of identifying various network intrusion behaviors
Efficient Fine-tuning
Fine-tuned on specific network intrusion detection datasets to improve detection accuracy
Model Capabilities
Network Traffic Analysis
Anomaly Behavior Detection
Security Threat Identification
Use Cases
Cybersecurity
Intrusion Detection System
Deployed at network boundaries for real-time monitoring and detection of intrusion behaviors
Security Log Analysis
Analyzes network device logs to identify potential security incidents
Featured Recommended AI Models
Š 2025AIbase