Granted Patent B2

US 12,200,002 · App. 18/379,711 · Granted Jan 14, 2025

Inventors: Wesley Kenneth Cobb (The Woodlands, TX); Ming-Jung Seow (The Woodlands, TX); Curtis Edward Cole, Jr. (Spring, TX); Cody Shay Falcon (Katy, TX); Benjamin A. Konosky (Friendswood, TX); Charles Richard Morgan (Katy, TX); Aaron Poffenberger (Houston, TX); Thong Toan Nguyen (Richmond, TX)

Assignee: Intellective Ai, Inc.

H04L63/1425G06F40/226G06F40/242G06F40/289G06F40/30G06N20/00H04L63/1408G06F40/247G06F40/253G06F40/284G06F40/40

Abstract

Claims (45)

1. A method, comprising:

generating, at a processor, a stable neuro-linguistic model by:

clustering a stream of normalized values to form a plurality of clusters,

building a dictionary of words based on the plurality of clusters, each word from the dictionary of words having a length from a plurality of lengths, each length from the plurality of lengths being less than or equal to a specified maximum letter length, and

generating a plurality of phrases based on the dictionary of words;

detecting, at the processor and using a codelet template, a pattern in a linguistic representation of information security data associated with a computer network, the linguistic representation of the information security data including at least one of (1) an ordered sequence of letters based on the plurality of clusters, or (2) the plurality of phrases;

receiving, at the processor, an ordered stream of normalized values associated with the information security data; and

sending alert data to a compute device, based on an output of the stable neuro-linguistic model, the pattern, and the ordered stream of normalized values, for display via the compute device.

2. The method of claim 1 , wherein the information security data includes one of security log data, disk mount data, physical access data, disk input/output log data, internet protocol (IP) address log data, security tool data, memory usage data, routing data, packet traffic data, datagram traffic data, segment traffic data, port traffic data, or Simple Network Management Protocol (SNMP) trap data.

3. The method of claim 1 , wherein each normalized value from the ordered stream of normalized values is associated with a value of the information security data and within a range of 0 to 1, inclusive.

4. The method of claim 1 , wherein the alert is indicative of a detected anomaly.

5. A non-transitory computer-readable storage medium storing processor-executable instructions to:

generate a stable neuro-linguistic model by:

clustering a stream of values to form a plurality of clusters,

generating a plurality of symbol combinations based on the plurality of clusters, and

generating a plurality of phrases based on the plurality of symbol combinations;

detect a pattern in a linguistic representation of information security data associated with a computer network, the linguistic representation of the information security data including at least one of: (1) an ordered sequence of symbols based on the plurality of clusters, (2) the plurality of symbol combinations, or (3) the plurality of phrases;

receive an ordered stream of values associated with the information security data, the ordered stream of values including Simple Network Management Protocol (SNMP) trap data; and

send alert data to at least one compute device within the computer network, based on an output of the stable neuro-linguistic model, the pattern, and the ordered stream of values, for display via the at least one compute device.

6. The non-transitory computer-readable storage medium of claim 5 , wherein the stream of values is received from a first compute device of the computer network, and the ordered stream of values is received from a second compute device of the computer network, the second compute device different from the first compute device.

7. The non-transitory computer-readable storage medium of claim 5 , further storing processor-executable instructions to:

build a dictionary of words based on the ordered sequence of symbols, each word from the dictionary of words having a length from a plurality of lengths, each length from the plurality of lengths being less than or equal to a specified maximum length.

8. The non-transitory computer-readable storage medium of claim 5 , wherein each value from the stream of values is associated with a value of the information security data.

9. The non-transitory computer-readable storage medium of claim 5 , wherein the alert is indicative of a detected anomaly associated with the computer network.

10. The non-transitory computer-readable storage medium of claim 5 , wherein:

the instructions to generate the stable neuro-linguistic model include instructions to generate a syntax, based on probabilistic relationships between symbol combinations from the plurality of symbol combinations, and

the instructions to detect the pattern in the linguistic representation of the information security data associated with the computer network include instructions to detect the pattern based on the syntax.

11. A system, comprising:

a processor; and

a memory storing instructions executable by the processor to:

generate a stable neuro-linguistic model by:

clustering a stream of values to form a plurality of clusters,

generating an ordered sequence of letters based on the plurality of clusters,

building a dictionary of words based on the ordered sequence of letters, each word from the dictionary of words having a length from a plurality of lengths, each length from the plurality of lengths being no greater than a specified maximum letter length, and

generating a plurality of phrases based on the dictionary of words, the stable neuro-linguistic model including at least one of the dictionary of words or the plurality of phrases; and

send alert data, based on an output of the stable neuro-linguistic model, to a compute device for display thereon.

12. The system of claim 11 , wherein each normalized value from the ordered stream of normalized values is associated with a value of the information security data and within a range of 0 to 1, inclusive.

13. The system of claim 11 , wherein the instructions to generate the stable neuro-linguistic model include instructions to generate a syntax, based on probabilistic relationships between words from the dictionary of words, the memory further storing instructions executable by the processor to detect, based on the syntax, an anomaly in an output of the stable neuro-linguistic model.

14. A non-transitory computer-readable storage medium storing processor-executable instructions to cause a processor to:

detect a pattern in a linguistic representation of information security data associated with a computer network, the linguistic representation of the information security data including at least one of an ordered sequence of symbols, a plurality of symbol combinations of a stable neuro-linguistic model, or a plurality of phrases of the stable neuro-linguistic model;

receive an ordered stream of values associated with the information security data, the ordered stream of values including Simple Network Management Protocol (SNMP) trap data; and

send alert data to at least one compute device within the computer network based on an output of the stable neuro-linguistic model, the pattern, and the ordered stream of values, for display via the at least one compute device.

15. The non-transitory computer-readable storage medium of claim 14 , wherein the information security data includes information security data associated with at least one of packet traffic, a disk mount event, or a physical access event, occurring within the computer network.

16. The non-transitory computer-readable storage medium of claim 14 , wherein the instructions to receive the ordered stream of values include instructions to receive the ordered stream of values via an information security plug-in located at the at least one compute device within the computer network.

17. The non-transitory computer-readable storage medium of claim 14 , wherein the alert is indicative of a detected anomaly associated with the computer network.

Assignments (5)

Continuity (8)

References Cited (238)

Cited By (1)

US 12,470,580