Cyber security system and method

Patent metadata

Field	Value
Publication number	US-12166795-B2
Application number	US-202117911853-A
Country	US
Kind code	B2
Filing date	Mar 8, 2021
Priority date	Mar 19, 2020
Publication date	Dec 10, 2024
Grant date	Dec 10, 2024

Abstract

A cyber security system creates a behavioral framework for evaluating the cyber security of an organization's computer systems based on its employees. The system leverages offline and online individual identity information and then translates this data to anonymous identifiers to protect privacy. The identifiers are used to pull data from an identity graph, which includes behavioral data. A business-to-business identity graph correlates the name of an organization that maintains the targeted computer system with the anonymous identifiers of employees. Online activity is gathered by pixels fired from websites accessed by user browsers and gathered by one or more remote servers.

First claim

The invention claimed is:

1. A cyber security system, comprising:
An identity compute cluster, wherein the identity compute cluster is configured to perform identity resolution for a plurality of objects, strip all personally identifiable information (PII) from the data pertaining to risk behaviors for the objects, associate an anonymized link associated with each of the objects for which there is data pertaining to risk behaviors, wherein the anonymized link does not contain any PII, and to output anonymized data pertaining to risk behaviors for the objects and append the anonymized link to corresponding data pertaining to risk behavior for each such object;
a pixel service compute cluster, wherein the pixel service compute cluster is configured to receive online activity data from a plurality of sources, associate the online activity data with particular devices, and output the online activity data associated with particular devices to the identity compute cluster;
a behavioral identity compute cluster, wherein the behavioral identity compute cluster is configured to receive behavioral data and associate the behavioral data with particular entities, and output behavioral data associated with particular entities to the identity compute cluster; and
a risk scoring compute cluster, wherein the risk scoring compute cluster is configured to receive the anonymized data pertaining to risk behaviors for the objects from the identity compute cluster; calculate trait scores for a plurality of cyber risk traits, wherein the cyber risk traits comprise at least financial risk-taking, social risk-taking, recreational risk-taking, conscientiousness, and decision making; group the trait scores into behavioral buckets, wherein the behavioral buckets include at least risk propensity, decision making, and personality; calculate behavioral bucket scores by performing a weighted sum of the trait scores within each behavioral bucket; compute a cyber security score based on a weighted sum of the behavioral bucket scores; and
generate a report.

2. The cyber security system of claim 1 , wherein the risk scoring compute cluster is further configured to receive feedback from a business computing system and re-calculate the cyber security score and report utilizing the feedback.

3. The cyber security system of claim 2 , wherein the risk scoring compute cluster is further configured to re-calculate the cyber security score and report in real time.

4. The cyber security system of claim 1 , further comprising a business-to-business (B2B) identity graph, wherein the identity compute cluster is configured to perform identity resolution for the plurality of objects by comparing data received at the identity compute cluster against the B2B identity graph.

5. The cyber security system of claim 4 , wherein the B2B identity graph comprises a plurality of nodes wherein each node corresponds to a business entity, and a node exists for all business entities of a segment within a particular region.

6. The cyber security system of claim 1 , further comprising a behavioral data platform configured to provide behavioral data to the behavioral identity compute cluster.

7. The cyber security system of claim 6 , wherein the behavioral identity compute cluster is further configured to collect device behavioral activity associated with an object.

8. The cyber security system of claim 7 , wherein the behavioral identity compute cluster is further configured to collect one or both of firmographic and behavioral data.

9. The cyber security system of claim 1 , further comprising a partner platform, wherein the partner platform comprises a set of records each pertaining to a particular object associated with an entity and each record comprises PII associated with the particular object.

10. The cyber security system of claim 9 , wherein the partner platform is configured to provide Internet protocol (IP) address data to the pixel service compute cluster.

11. The cyber security system of claim 10 , wherein the partner platform comprises a plurality of employee electronic devices, wherein the employee electronic devices comprise a web browser configured to send browsing data to the pixel service compute cluster.

12. A method for assessing cyber security of a partner 15 . platform, comprising:
at the partner platform, creating a set of records each pertaining to a particular object associated with an entity wherein each record comprises PII associated with the particular object;
at an identity compute cluster, performing identity resolution for a plurality of objects, and outputting anonymized data pertaining to risk behaviors for the objects;
at a pixel service compute cluster, receiving a set of Internet protocol (IP) address data from the partner platform, matching online activity data from a plurality of sources with particular electronic devices, and outputting the online activity data associated with the particular electronic devices to the identity compute cluster;
at a behavioral identity compute cluster, matching the behavioral data to particular entities, and outputting behavioral data associated with particular entities to the identity compute cluster; and
at a risk scoring compute cluster, matching against the behavioral data using a list of segments associated with cyber risk, clustering the segments into trait categories and performing a weighted sum of the trait categories to compute a cyber security score from the behavioral data associated with particular entities, wherein the segments comprise at least financial risk-taking, social risk-taking, recreational risk-taking, conscientiousness, and decision making, and wherein the trait categories comprise at least risk propensity, decision making, and personality.

13. The method of claim 12 , further comprising the steps of generating feedback at the partner platform and re-calculating the cyber security score utilizing the feedback.

14. The method of claim 13 , wherein the step of re-calculating the cyber security score is performed in real time.

15. The method of claim 12 , further comprising the steps of stripping all personally identifiable data (PII) from the data pertaining to risk behaviors for the objects, associating an anonymized link associated with each of the objects for which there is data pertaining to risk behaviors, and appending the anonymized link to corresponding data pertaining to risk behavior for each such object.

16. The method of claim 12 , further comprising the step of performing firm identity resolution for the plurality of objects by comparing data received at the identity compute cluster against a business-to-business (B2B) identity graph.

17. The method of claim 12 , further comprising the step of sending browsing data from a web browser to the pixel service compute cluster.

18. The method of claim 12 , wherein the step of matching at the risk scoring compute cluster comprises string matching to identify segments associated with cyber risk.

19. The method of claim 12 , wherein the step of matching at the risk scoring compute cluster comprises natural language processing (NLP) to identify segments associated with cyber risk and performing clustering of the segments into the trait categories using principal components analysis (PCA).

20. A system for managing cyber risk, comprising:
an identity compute cluster, wherein the identity compute cluster is configured to perform identity resolution for a plurality of objects, strip all personally identifiable data pertaining to risk behaviors

Assignees

• Liveramp Inc

Inventors

• Boyle Rachael
• Huang Lucy
• Cramer Lisa

Classifications

• H04L2463/146

  Tracing the source of attacks · CPC title

• H04L63/1425

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

• H04L63/1483 Primary

  service impersonation, e.g. phishing, pharming or web spoofing (detection of rogue wireless access points H04W12/12) · CPC title

• G06F21/577 Primary

  Assessing vulnerabilities and evaluating computer system security · CPC title