About this Video

• Video Title: An Internet-wide view of CG-NAT and Large-scale IP Sharing | Cloudflare Research | LACNIC 43
• Channel: Giotsas
• Speakers: Vasilis (primary speaker), Nick and Antoine (mentioned)
• Duration: 00:15:28

Introduction

This video presents research on detecting and analyzing large-scale IP sharing, focusing on Carrier-Grade NAT (CG-NAT) and VPNs. The speaker discusses the challenges of collateral damage from IP-based filtering and the disproportionate impact on developing countries due to higher IP sharing. The core purpose is to explain a method for identifying CG-NAT and VPN IPs to minimize the negative effects of security filtering.

Key Takeaways

• IP-based security filtering (blocking known attackers, rate limiting) causes collateral damage: Blocking an IP address affects all users sharing that address (CG-NAT), leading to unfair consequences for innocent users.
• CG-NAT and VPNs disproportionately affect developing countries: Developing nations often have more users sharing fewer IP addresses, making them more vulnerable to the negative effects of security filtering.
• A machine learning model is used to identify CG-NAT and VPN IPs: The model analyzes various features from millions of daily requests to distinguish between CG-NAT, VPN, and other IP types with 98% accuracy.
• Key features used for IP classification include: request volume, client diversity, browser/device diversity, TLS fingerprint diversity, RTT variability.
• An IETF draft proposal suggests ISPs self-report CG-NAT IPs: This would improve the accuracy of security filtering by providing more precise data to content providers.

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