About this document

Real-Time Crawler Detection Methodology by beam.mild is a document available to read on EtoBox.

The document presents a methodology for real-time detection of web crawlers using decision trees and machine learning techniques to classify requests as originating from crawlers or human users. The system processes incoming HTTP requests, analyzes session features, and utilizes a Bayesian network for classification, demonstrating effective results in distinguishing between crawlers and humans. Experimental results indicate that the system achieves high recall and precision rates, making it a promising appr

Author

beam.mild

Language

EN