Scalable inline behavioral DDoS attack mitigation

• US 10,419,490 B2
• Filed: 06/30/2017
• Issued: 09/17/2019
• Est. Priority Date: 07/16/2013
• Status: Active Grant

• Current Assignee: Fortinet Inc.
• Original Assignee: Fortinet Inc.
• Inventors: Jain, Hemant Kumar
• Primary Examiner(s): Pwu, Jeffrey C
• Assistant Examiner(s): Tran, Baotram
• Application Number:
  US15/640,233
• Publication Number:
  US 20170302698A1
• Time in Patent Office: 809 Days
• Field of Search: None
• CPC Class Codes: H04L 63/1416 Event detection, e.g. attack signature detection
• CPC Class Codes: H04L 63/1425 Traffic logging, e.g. anomaly detection
• CPC Class Codes: H04L 63/1458 Denial of Service
• CPC Class Codes: H04L 63/20 for managing network security; network security policies in general filtering policies H04L63/0227

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.

Claims

1. A method comprising:

receiving, by a switch of a Distributed Denial of Service (DDoS) attack mitigation appliance, packets from an external network and destined for an internal network protected by the DDoS attack mitigation appliance;

remembering, by the switch, respective ports of the DDoS attack mitigation appliance on which the packets were received to facilitate forwarding of the packets on corresponding pair ports of the DDoS attack mitigation appliance after the packets are processed by a plurality of DDoS attack mitigation components of the DDoS attack mitigation appliance;

providing improved throughput over that which is achievable by a single, inline DDoS attack mitigation component, by distributing, by the switch, the 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 one or more of individual protocols with which the packets are associated and individual parameters or commands of the individual protocols;

obtaining, by a controlling host of the DDoS attack mitigation appliance, from each of the plurality of DDoS attack mitigation components, the plurality of granular rates;

continuously and adaptively adjusting, 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 and based on one or more of corresponding historical base rates, trends and seasonality;

causing, by the controlling host, the plurality of DDoS attack mitigation components to perform DDoS attack mitigation including enforcement of the plurality of granular rate thresholds by configuring the DDoS attack mitigation components with the plurality of granular rate thresholds; and

performing granular rate limiting of the packets to the plurality of granular rate thresholds for each of the plurality of layer 2, layer 3, layer 4 and layer 7 parameters by forwarding or dropping, by the plurality of DDoS attack mitigation components, the packets based on results of the DDoS attack mitigation.

2. The method of claim 1, further comprising:

temporarily storing, by each of the plurality of DDoS attack mitigation components, the packets; and

forwarding or dropping, by each of the plurality of DDoS attack mitigation components, the 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 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 rate of Address Resolution Protocol (ARP) packets or Reverse ARP (RARP) packets within the 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 rate of broadcast packets, non-Internet Protocol (IP) packets or Virtual Local Area Network (VLAN)-tagged packets within the 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 of a particular protocol, a particular Internet Protocol (IP) option or fragmented packets within the 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 packets are originated within the external network.

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 packets are directed within the internal network.

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 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 of SYN, ACK, FIN, PUSH or RST packets within the 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 of SYN, ACK, FIN, PUSH or RST packets within the packets that are received 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 of SYN, ACK, FIN, PUSH or RST packets within the 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 of 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 within the packets.

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 of a particular Session Initiation Protocol (SIP) method, a particular SIP URL or a particular SIP user-agent within the packets.

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 of Domain Name System (DNS) queries or DNS responses within the packets.