Method and system for tracking machines on a network using fuzzy guid technology

• US 9,449,168 B2
• Filed: 06/06/2014
• Issued: 09/20/2016
• Est. Priority Date: 11/28/2005
• Status: Active Grant

• Current Assignee: Threatmetrix Incorporated (RELX PLC)
• Original Assignee: Threatmetrix Incorporated (RELX PLC)
• Inventors: Thomas, Scott, Jones, David G.
• Primary Examiner(s): HERZOG, MADHURI R
• Application Number:
  US14/298,823
• Publication Number:
  US 20150074804A1
• Time in Patent Office: 837 Days
• Field of Search: 726 22- 25, 709217-229
• US Class Current: 1/1
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 21/00 Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
• CPC Class Codes: G06F 21/50 Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
• CPC Class Codes: G06F 21/55 Detecting local intrusion or implementing counter-measures
• CPC Class Codes: G06F 21/57 Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
• CPC Class Codes: G06F 2201/86 Event-based monitoring
• CPC Class Codes: G06F 2221/2127 Bluffing
• CPC Class Codes: H04L 2463/146 Tracing the source of attacks
• CPC Class Codes: H04L 63/0236 Filtering by address, protocol, port number or service, e.g. IP-address or URL
• 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 63/10 for controlling access to devices or network resources
• CPC Class Codes: H04L 63/14 for detecting or protecting against malicious traffic
• CPC Class Codes: H04L 63/1408 by monitoring network traffic monitoring network traffic per se H04L43/00
• CPC Class Codes: H04L 63/1441 Countermeasures against malicious traffic countermeasures against attacks on cryptographic mechanisms H04L9/002

Abstract

A method for querying a knowledgebase of malicious hosts numbered from 1 through N. The method includes providing a network of computers, which has a plurality of unknown malicious host machines. In a specific embodiment, the malicious host machines are disposed throughout the network of computers, which includes a worldwide network of computers, e.g., Internet. The method includes querying a knowledge base including a plurality of known malicious hosts, which are numbered from 1 through N, where N is an integer greater than 1. In a preferred embodiment, the knowledge base is coupled to the network of computers. The method includes receiving first information associated with an unknown host from the network; identifying an unknown host and querying the knowledge base to determine if the unknown host is one of the known malicious hosts in the knowledge base. The method also includes outputting second information associated with the unknown host based upon the querying process.

Claims

1. A method tracking machines on a network of computers, the method comprising:

identifying a malicious host coupled to the network of computers;

determining a first IP address and one or more first attributes associated with the malicious host during a first time period, wherein the one or more first attributes includes first behavior information associated with the malicious host during the first time period;

classifying the malicious host to be in a determined state;

determining that the malicious host is in a latent state during a second time periods;

identifying an unknown host during the second time period when the malicious host is in the latent state, the unknown host being associated with a second IP address and one or more second attributes, wherein the one or more second attributes includes second behavior information associated with the unknown host during the second time period;

processing the second IP address and the one or more second attributes of the unknown host with the first IP address and the one or more first attributes of the malicious host; and

determining if the unknown host is the malicious host based on results of the processing of the second IP address and the one or more second attributes of the unknown host with the first IP address and the one or more first attributes of the malicious host.

2. The method of claim 1 wherein the one or more attributes comprises an IP range, ISP, country, ISP practice, or range class within the ISP.

3. The method of claim 1 wherein the network of computers includes a world wide network of computers.

4. The method of claim 1 further comprising determining if the unknown host is a different machine than the malicious host.

9. The method of claim 4 wherein the identifying of the unknown host further comprising:

determining a plurality of identity attributes;

assigning a quality measure to each of the plurality the identity attributes;

collecting one or more evidences from the unknown host;

determining an attribute fuzzy GUID for each of the plurality of identity attributes for the unknown host, the attribute fuzzy GUID being associated with the evidences;

processing the attribute fuzzy GUID for each of the plurality of attributes to determine a host fuzzy GUID for the unknown host.

10. The method of claim 9 wherein the one or more attributes comprises an IP range, ISP, country, ISP practice, or range class within the ISP.

11. The method of claim 9 further comprising selecting a second plurality of identity attributes characterized by quality measures higher than a predetermined value.

5. A method for querying a knowledgebase of malicious hosts numbered from 1 through N, the method comprising:

providing a network of computers, the network of computers including a plurality of unknown malicious host machines, the malicious host machines being disposed throughout the network of computers, the network of computers including a world wide network of computers;

querying a knowledge base including a plurality of known malicious hosts, the plurality of known malicious hosts being numbered from 1 through N, where N is an integer greater than 1, the knowledge base being coupled to the network of computers;

receiving first information associated with an unknown host from the network wherein the first information includes behavior information associated with the unknown host;

identifying the unknown host based on the first information;

querying the knowledge base to determine if the unknown host is one of the known malicious hosts in the knowledge base using the first information including the behavior information associated with the unknown host; and

outputting second information associated with the unknown host based upon the querying process.

6. The method of claim 5 wherein N is an integer three million or more.

7. The method of claim 5 further comprising, if the unknown host is one of the known malicious hosts, updating a filter to block access of the malicious host to one or more segments of the network of computers.

8. The method of claim 5 further comprising outputting an alert to signify the malicious host, if the unknown host is determined to be one of the malicious hosts.

12. A computer based method for populating a database to form a knowledge base of malicious host entities, the method comprising:

determining a plurality of identity attributes;

assigning a quality measure to each of the plurality of identity attributes;

collecting one or more evidences from the unknown host, wherein the one or more evidences includes behavior information associated with the unknown host;

determining an attribute fuzzy GUID for each of the plurality of identity attributes for the unknown host based on the one or more evidences, wherein the attribute fuzzy GUID for each of the plurality of identity attributes including a first attribute fuzzy GUID determined based on the behavior information;

processing the attribute fuzzy GUID for each of the plurality of attributes to determine a host fuzzy GUID for the unknown host; and

storing the host fuzzy GUID for the unknown host in one or more memories of a database to form a knowledge base.

13. The method of claim 12 wherein the one or more attributes comprises an IP range, ISP, country, ISP practice, or range class within the ISP.

14. The method of claim 12 further comprising selecting a second plurality of identity attributes characterized by quality measures higher than a predetermined value.

15. A computer based system for populating a database to form a knowledge base of malicious host entities, the system comprising a machine readable memory or memories, the memory or memories comprising:

one or more codes directed to determining a plurality of identity attributes;

one or more codes directed to assigning a quality measure to each of the plurality the identity attributes;

one or more codes directed to collecting one or more evidences from the unknown host, wherein the one or more evidences includes behavior information associated with the unknown host;

one or more codes directed to determining an attribute fuzzy GUID for each of the plurality of identity attributes for the unknown host based on the one or more evidences, wherein the attribute fuzzy GUID for each of the plurality of identity attributes includes a first attribute fuzzy GUID determined based on the behavior information;

one or more codes directed to processing the attribute fuzzy GUID for each of the plurality of attributes to determine a host fuzzy GUID for the unknown host; and

one or more codes directed to storing the host fuzzy GUID for the unknown host in one or more memories of a database to form a knowledge base.

16. The system of claim 15 wherein the unknown host is one of a plurality of computing devices in a world wide network of computers.

17. The system of claim 15 wherein the one or more codes directed to storing is an executable code.

18. The system of claim 15 wherein the knowledge base comprises a plurality of malicious host information.

19. The system of claim 15 wherein the host fuzzy GUID comprises an identifier.

20. The system of claim 19 wherein the identifier is an IP address.