Scalable inline behavioral DDoS attack mitigation

Patent metadata

Field	Value
Publication number	US-9699211-B2
Application number	US-201514815261-A
Country	US
Kind code	B2
Filing date	Jul 31, 2015
Priority date	Jul 16, 2013
Publication date	Jul 4, 2017
Grant date	Jul 4, 2017

Abstract

Methods and systems for a scalable solution to behavioral Distributed Denial of Service (DDoS) attacks targeting a network are provided. According to one embodiment, a method to determine the scaling treatment is provided for various granular layer parameters of the Open System Interconnection (OSI) model for communication systems. A hardware-based apparatus helps identify packet rates and determine packet rate thresholds through continuous and adaptive learning with multiple DDoS attack mitigation components. The system can be scaled up by stacking multiple DDoS attack mitigation components to provide protection against large scale DDoS attacks by distributing load across these stacked components.

First claim

What is claimed is:

1. A method comprising:
receiving, by a switch, inbound/outbound packets;
remembering, by the switch, ports on which the inbound/outbound packets were received to facilitate forwarding of the inbound/outbound packets on corresponding pair ports after the inbound/outbound packets are processed by a plurality of Distributed Denial of Service (DDoS) attack mitigation components;
distributing, by the switch, the inbound/outbound packets among the plurality of DDoS attack mitigation components;
calculating, by each of the plurality of DDoS attack mitigation components, a plurality of granular rates for each of a plurality of Open System Interconnection (OSI) model network layers, including a plurality of layer 2, layer 3, layer 4 and layer 7 parameters, based on individual protocols, individual parameters or commands of the individual protocols of the inbound/outbound packets;
sending, by each of the plurality of DDoS attack mitigation components, the plurality of granular rates to a controlling host;
generating, by the controlling host, a plurality of granular rate thresholds for each of the plurality of layer 2, layer 3, layer 4 and layer 7 parameters by aggregating corresponding granular rates of the plurality of granular rates;
sending, by the controlling host, the plurality of granular rate thresholds to the plurality of DDoS attack mitigation components;
responsive to receipt of the plurality of granular rate thresholds, performing, by the plurality of DDoS attack mitigation components, DDoS attack mitigation by enforcing the plurality of granular rate thresholds; and
forwarding or dropping, by the plurality of DDoS attack mitigation components, the inbound/outbound packets based on results of the DDoS attack mitigation, whereby the inbound/outbound packets are rate limited granularly to the plurality of granular rate thresholds for each of the plurality of layer 2, layer 3, layer 4 and layer 7 parameters.

2. The method of claim 1 , further comprising:
temporarily storing, by each of the plurality of DDoS attack mitigation components, the inbound/outbound packets; and
forwarding or dropping, by each of the plurality of DDoS attack mitigation components, the inbound/outbound packets based on a decision by a continuous and adaptive granular rate anomaly engine.

3. The method of claim 1 , further comprising determining, by a continuous and adaptive granular rate anomaly engine of each of the plurality of DDoS attack mitigation components, the plurality of granular rates based on packet meta information of the inbound/outbound packets.

4. The method of claim 3 , further comprising sending, by the continuous and adaptive granular rate anomaly engine of each of the plurality of DDoS attack mitigation components, granular network layer drop statistics to the controlling host over a host interface.

5. The method of claim 3 , further comprising setting, by the continuous and adaptive granular rate anomaly engine of each of the plurality of DDoS attack mitigation components, the plurality of granular rate thresholds based on commands received from the controlling host over a host interface.

6. The method of claim 1 , further comprising combining, by the controlling host, the corresponding granular rates from the plurality of DDoS attack mitigation components by using a plurality of corresponding scaling treatments to arrive at an effective rate to be used for adaptive threshold calculation.

7. The method of claim 1 , wherein a layer 2 granular rate of the plurality of granular rates for layer 2 parameters comprises an observed packet rate within the inbound/outbound packets for Address Resolution Protocol (ARP) packets or Reverse ARP (RARP) packets.

8. The method of claim 1 , wherein a layer 2 granular rate of the plurality of granular rates for layer 2 parameters comprises an observed packet rate within the inbound/outbound packets for broadcast packets, non-Internet Protocol (IP) packets or Virtual Local Area Network (VLAN)-tagged packets.

9. The method of claim 1 , wherein a layer 3 granular rate of the plurality of granular rates for layer 3 parameters comprises an observed packet rate within the inbound/outbound packets for a particular protocol, a particular Internet Protocol (IP) option or fragmented packets.

10. The method of claim 1 , wherein a layer 3 granular rate of the plurality of granular rates for layer 3 parameters comprises an observed packet rate for a most active source from which the inbound/outbound packets are originated.

11. The method of claim 1 , wherein a layer 3 granular rate of the plurality of granular rates for layer 3 parameters comprises an observed packet rate for a most active destination to which the inbound/outbound packets are directed.

12. The method of claim 1 , wherein a layer 3 granular rate of the plurality of granular rates for layer 3 parameters comprises a count of unique sources specified by the inbound/outbound packets.

13. The method of claim 1 , wherein a layer 4 granular rate of the plurality of granular rates for layer 4 parameters comprises an observed packet rate within the inbound/outbound packets for SYN, ACK, FIN, PUSH or RST packets.

14. The method of claim 1 , wherein a layer 4 granular rate of the plurality of granular rates for layer 4 parameters comprises an observed packet rate within the inbound/outbound packets for SYN, ACK, FIN, PUSH or RST packets that are from a particular source.

15. The method of claim 1 , wherein a layer 4 granular rate of the plurality of granular rates for layer 4 parameters comprises an observed packet rate within the inbound/outbound packets for SYN, ACK, FIN, PUSH or RST packets that are directed to a particular destination.

16. The method of claim 1 , wherein a layer 4 granular rate of the plurality of granular rates for layer 4 parameters comprises an observed total number of established connections to a particular destination.

17. The method of claim 1 , wherein a layer 4 granular rate of the plurality of granular rates for layer 4 parameters comprises an observed number of concurrent connections to a particular destination or from a particular source.

18. The method of claim 1 , wherein a layer 7 granular rate of the plurality of granular rates for layer 7 parameters comprises an observed rate within the inbound/outbound packets for a particular Hypertext Transfer Protocol (HTTP) method, a particular HTTP Uniform Resource Locator (URL), a particular HTTP user-agent or a particular HTTP URL from a particular source.

19. The method of claim 1 , wherein a layer 7 granular rate of the plurality of granular rates for layer 7 parameters comprises an observed rate within the inbound/outbound packets for a particular Session Initiation Protocol (SIP) method, a particular SIP URL or a particular SIP user-agent.

20. The method of claim 1 , wherein a layer 7 granular rate of the plurality of granular rates for layer 7 parameters comprises an observed rate within the inbound/outbound packets for Domain Name System (DNS) queries or DNS responses.

Assignees

• Fortinet Inc

Inventors

• Jain Hemant Kumar

Classifications

• H04L63/20 Primary

  for managing network security; network security policies in general (filtering policies H04L63/0227) · CPC title

• H04L63/1458 Primary

  Denial of Service · CPC title

• H04L63/1416

  Event detection, e.g. attack signature detection · CPC title

• H04L63/1425

  Traffic logging, e.g. anomaly detection · CPC title