Training a million models per day to save customers of all sizes from DDoS attacks
Our always-on DDoS protection runs inside every server across our global network. It constantly analyzes incoming traffic, looking for signals associated with previously identified DDoS attacks. We dynamically create fingerprints to flag malicious traffic, which is dropped when detected in high enough volume — so it never reaches its destination — keeping customer websites online.
In many cases, flagging bad traffic can be straightforward. For example, if we see too many requests to a destination with the same protocol violation, we can be fairly sure this is an automated script, rather than a surge of requests from a legitimate web browser.
Our DDoS systems are great at detecting attacks, but there’s a minor catch. Much like the human immune system, they are great at spotting attacks similar to things they have seen before. But for new and novel threats, they need a little help knowing what to look for, which is an expensive and time-consuming human endeavor.
Cloudflare protects millions of Internet properties, and we serve over 60 million HTTP requests per second on average, so trying to find unmitigated attacks in such a huge volume of traffic is a daunting task. In order to protect the smallest of companies, Continue reading
