EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hacker News·Sep 7·5 min read
Bot Detection Without JavaScript: What My Blog Measured
TL;DR
A blog implemented network and request-header rules to effectively identify 74.5% of bot traffic, enhancing traffic analysis for a Cloudflare Worker. This method revealed misclassifications and improved request validation.
✦ Why It Matters
Implement network and request-header rules to improve bot detection and traffic analysis today.
Key Takeaways
- Classify requests using network and header rules to identify bots.
- Analyze discrepancies between page events and visit metrics.
- Improve traffic analysis by understanding automated request patterns.
- Ensure transparency in how content is consumed by automated agents.
How It Works
The classification system uses network metadata, Fetch Metadata, and User-Agent strings to categorize requests. It distinguishes between legitimate browser traffic and automated requests by applying specific rules that account for known hosting networks and missing metadata.
This allows for a more accurate understanding of web traffic.