ANOMALY DETECTION THROUGH HEADER FIELD ENTROPY

• US 20160359881A1
• Filed: 06/03/2016
• Published: 12/08/2016
• Est. Priority Date: 06/05/2015
• Status: Active Grant

• Current Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Original Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Inventors: Yadav, Navindra, Alizadeh Attar, Mohammadreza, Gandham, Shashidhar, Pang, Jackson Ngoc Ki, Spadaro, Roberto Fernando
• Granted Patent: US 10,623,283 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/122 using management policies backup systems G06F11/1446; file migration policies for HSM systems G06F16/185
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• CPC Class Codes: G06N 99/00 : Subject matter not provided for in other groups of this subclass
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• CPC Class Codes: H04L 1/242 : by comparing a transmitted test signal with a locally generated replica
• CPC Class Codes: H04L 41/046 : comprising network management agents or mobile agents therefor
• CPC Class Codes: H04L 41/0668 : by dynamic selection of recovery network elements, e.g. replacement by the most appropriate element after failure
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• CPC Class Codes: H04L 43/026 : using flow identification
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• CPC Class Codes: H04L 43/062 : related to network traffic
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• CPC Class Codes: H04L 43/12 : Network monitoring probes
• CPC Class Codes: H04L 43/16 : Threshold monitoring
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• CPC Class Codes: H04L 45/306 : Route determination based on the nature of the carried application
• CPC Class Codes: H04L 45/38 : Flow based routing
• CPC Class Codes: H04L 45/46 : Cluster building
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• CPC Class Codes: H04L 47/11 : Identifying congestion
• CPC Class Codes: H04L 47/20 : Traffic policing
• CPC Class Codes: H04L 47/2441 : relying on flow classification, e.g. using integrated services [IntServ]
• CPC Class Codes: H04L 47/2483 : involving identification of individual flows
• CPC Class Codes: H04L 47/28 : in relation to timing considerations
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• CPC Class Codes: H04L 61/5007 : Internet protocol [IP] addresses
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• CPC Class Codes: H04L 63/0263 : Rule management
• CPC Class Codes: H04L 63/06 : for supporting key management in a packet data network cryptographic mechanisms or cryptographic arrangements for key management H04L9/08
• CPC Class Codes: H04L 63/0876 : based on the identity of the terminal or configuration, e.g. MAC address, hardware or software configuration or device fingerprint
• CPC Class Codes: H04L 63/1408 : by monitoring network traffic monitoring network traffic per se H04L43/00
• 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 63/1433 : Vulnerability analysis
• CPC Class Codes: H04L 63/1441 : Countermeasures against malicious traffic countermeasures against attacks on cryptographic mechanisms H04L9/002
• CPC Class Codes: H04L 63/145 : the attack involving the propagation of malware through the network, e.g. viruses, trojans or worms
• CPC Class Codes: H04L 63/1458 : Denial of Service
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• CPC Class Codes: H04L 63/16 : Implementing security features at a particular protocol layer
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• CPC Class Codes: H04L 67/01 : Protocols
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• CPC Class Codes: H04L 67/1001 : for accessing one among a plurality of replicated servers
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• CPC Class Codes: H04L 67/535 : Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04L 67/75 : Indicating network or usage conditions on the user display
• CPC Class Codes: H04L 69/16 : Implementation or adaptation of Internet protocol [IP], of transmission control protocol [TCP] or of user datagram protocol [UDP]
• CPC Class Codes: H04L 69/22 : Parsing or analysis of headers
• CPC Class Codes: H04L 7/10 : Arrangements for initial synchronisation
• CPC Class Codes: H04L 9/0866 : involving user or device identifiers, e.g. serial number, physical or biometrical information, DNA, hand-signature or measurable physical characteristics
• CPC Class Codes: H04L 9/3239 : involving non-keyed hash functions, e.g. modification detection codes [MDCs], MD5, SHA or RIPEMD
• CPC Class Codes: H04L 9/3242 : involving keyed hash functions, e.g. message authentication codes [MACs], CBC-MAC or HMAC
• CPC Class Codes: H04W 72/54 : based on quality criteria
• CPC Class Codes: H04W 84/18 : Self-organising networks, e.g. ad-hoc networks or sensor networks

Abstract

An approach for detecting anomalous flows in a network using header field entropy. This can be useful in detecting anomalous or malicious traffic that may attempt to “hide” or inject itself into legitimate flows. A malicious endpoint might attempt to send a control message in underutilized header fields or might try to inject illegitimate data into a legitimate flow. These illegitimate flows will likely demonstrate header field entropy that is higher than legitimate flows. Detecting anomalous flows using header field entropy can help detect malicious endpoints.

Claims

1. A computer-implemented method comprising:

detecting, using a sensor installed on an endpoint, a plurality of flows associated with the endpoint;

determining an entropy associated with a header field for the plurality of flows;

determining that the entropy is greater than a predetermined amount; and

determining that the plurality of flows is anomalous.

2. The computer-implemented method of claim 1, further comprising:

detecting a second plurality of flows;

determining that the second plurality of flows are regular; and

determining a second entropy associated with the header field for the second plurality of flows,

wherein the predetermined amount is based on the second entropy.

3. The computer-implemented method of claim 1, wherein the endpoint is a destination for the plurality of flows and the detecting of the plurality of flows comprises:

detecting, using a second sensor associated with a second endpoint, the plurality of flows, wherein the second endpoint is a source for the plurality of flows.

4. The computer-implemented method of claim 1, wherein the header field is the packet identification field of the Internet Protocol version 4 standard.

5. The computer-implemented method of claim 1, wherein the header field is a time to live field.

6. The computer-implemented method of claim 1, wherein the header field is a sequence identifier field.

7. The computer-implemented method of claim 6, wherein determining the entropy associated with the header field associated with the plurality of flows comprises:

determining an expected sequence identifier field for each of the plurality of flows; and

determining a difference between the expected sequence identifier field and the detected sequence identifier field.

8. A non-transitory computer-readable medium having computer readable instructions that, when executed by a processor of a computer, cause the computer to:

detect, using a sensor installed on an endpoint, a plurality of flows associated with the endpoint;

determine an entropy associated with a header field for the plurality of flows;

determine that the entropy is greater than a predetermined amount; and

determine that the plurality of flows is anomalous.

9. The non-transitory computer-readable medium of claim 8, wherein the instructions further cause the computer to:

detect a second plurality of flows;

determine that the second plurality of flows are regular; and

determine a second entropy associated with the header field for the second plurality of flows,

wherein the predetermined amount is based on the second entropy.

10. The non-transitory computer-readable medium of claim 8, wherein the endpoint is a destination for the plurality of flows and the instructions that cause the computer to detect the plurality of flows further cause the computer to:

detect, using a second sensor associated with a second endpoint, the plurality of flows, wherein the second endpoint is a source for the plurality of flows.

11. The non-transitory computer-readable medium of claim 8, wherein the header field is the packet identification field of the Internet Protocol version 4 standard.

12. The non-transitory computer-readable medium of claim 8, wherein the header field is a time to live field.

13. The non-transitory computer-readable medium of claim 8, wherein the header field is a sequence identifier field.

14. The non-transitory computer-readable medium of claim 13, wherein the instructions that cause the computer to determine the entropy associated with the header field associated with the plurality of flows further cause the computer to:

determine an expected sequence identifier field for each of the plurality of flows; and

determine a difference between the expected sequence identifier field and the detected sequence identifier field.

15. A system comprising:

a processor;

memory including instructions that when executed by the processor, cause the system to;

detect, using a sensor installed on an endpoint, a plurality of flows associated with the endpoint;

determine an entropy associated with a header field for the plurality of flows;

determine that the entropy is greater than a predetermined amount; and

determine that the plurality of flows is anomalous.

16. The system of claim 15, wherein the instructions further cause the system to:

detect a second plurality of flows;

determine that the second plurality of flows are regular; and

determine a second entropy associated with the header field for the second plurality of flows,

wherein the predetermined amount is based on the second entropy.

17. The system of claim 15, wherein the endpoint is a destination for the plurality of flows and wherein the instructions further cause the system to:

detect, using a second sensor associated with a second endpoint, the plurality of flows, wherein the second endpoint is a source for the plurality of flows.

18. The system of claim 15, wherein the instructions further cause the system to

wherein the header field is the packet identification field of the Internet Protocol version 4 standard.

19. The system of claim 15, wherein the header field is a time to live field.

20. The system of claim 15, wherein the header field is a sequence identifier field.