NetFlow Or sFlow For Fastest DDoS Detection?

It's still not an easy choice, but combined with the faster NetFlow exporters that have recently come to market, the speed advantage of sFlow is starting to fade.

Dr. Vincent Berk, Chief Strategy Officer, Quantum Xchange

January 26, 2016

3 Min Read

Successful distributed denial of service (DDoS) triage and mitigation depend on two things: speed of detection and accuracy of detection. When users are considering a DDoS solution, I am often asked if it is best to use NetFlow or sFlow. To understand what is best, we must first take a brief look at the differences between the two types of flow data.

NetFlow (and the very closely related cFlow, JFlow, and IPFIX) is a summary record format, where a router or other exporting device tabulates the statistics on each flow of packets flying by. A flow is typically defined as the 5-tuple of sending IP and port, receiving IP and port, and the protocol. Each packet is tabulated and added to the appropriate row in the table: 1 more packet, X more bytes. State is kept on every flow that the exporter observes, and when a flow is 60 seconds old, the record is sent to the collector, which has the task of detecting the denial of service attack.

sFlow takes a slightly different approach, keeping no state at all. Instead sFlow randomly grabs one in every N packets flying by and immediately sends it to the collector. Although this approach may appear somewhat less accurate than the NetFlow tabulation, it is actually very good for fast DDoS detection. As the flood or amplification attack starts to ramp up, the rate of packets flowing by the exporter starts to increase very rapidly. This means that the number of packet samples going to the collector (which is responsible for the DDoS detection) starts to increase immediately.

Although the NetFlow approach ensures that no packet is missed, which is great for accurate network forensics, the nature of the export timer may result in much slower detections. If the NetFlow exporter has sufficient memory to keep state on all the attack traffic, it may take up to 60 seconds before the detecting collector sees any evidence of the attack! Thankfully though, many newer NetFlow-capable devices can be tuned to export at higher rates, resulting in improved detection times.

Detection accuracy is another matter. Since both sFlow and NetFlow transmit information on sending and receiving port and both transmit information on flag combinations and IP addresses, it is really up to the collector to make an accurate detection. Distinguishing a DNS or NTP amplification attack from a SMURF, or a FRAGGLE attack from a SynFlood, is key in performing effective mitigation. Most triage scenarios (whether using a scrubbing device or manually mitigating) rely on knowing a couple of key factors:

  1. What are the targets being hit?

  2. Are the bit/packet rates sufficiently high to impact the service?

  3. What is the specific type (or types) of attack?

Both NetFlow as well as sFlow provide sufficient detail to accurately make that determination if the detection logic is present in the collector software.

In practice, I have seen both sFlow and NetFlow variants deployed very successfully in DDoS detection. Although I have seen sFlow deployments detect DDoS attacks in as little as 3 seconds, the nature of the Internet has made it such that it can take some time before the attack reaches full strength.

Combined with the faster NetFlow exporters that have recently started to reach the market, the speed advantage of sFlow is starting to fade. Also, keep in mind that many environments will not have a choice, as the exporting hardware is already in place, supporting only a single type of export. So the choice may not be yours, and both approaches can be used to tune and finesse for detection speed and accuracy. Most importantly, if you have both, then use both. The better the visibility, the better your defense.

About the Author(s)

Dr. Vincent Berk

Chief Strategy Officer, Quantum Xchange

Dr. Vincent Berk is Chief Strategy Officer at Quantum Xchange, the maker of Phio TX, a quantum-safe key delivery system. He is the former Chief Technology Officer and Chief Security Architect at Riverbed Technologies, a large network performance company, and has served as a computer science faculty member at Dartmouth College.

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