Systems and methods for determining individual and group risk scores

Patent metadata

Field	Value
Publication number	US-11108792-B2
Application number	US-202017121442-A
Country	US
Kind code	B2
Filing date	Dec 14, 2020
Priority date	May 16, 2018
Publication date	Aug 31, 2021
Grant date	Aug 31, 2021

Abstract

Embodiments disclosed herein describe a server, for example a security awareness server or an artificial intelligence machine learning system that establishes a risk score or vulnerable for a user of a security awareness system, or for a group of users of a security awareness system. The server may create a frequency score for a user, which predicts the frequency at which the user is to be hit with a malicious attack. The frequency score may be based on at least a job score, which may be represented by a value that is based on the type of job the user has, and a breach score that may be represented by a value that is based on the user's level of exposure to email.

First claim

We claim:

1. A method comprising:
identifying, by one or more processors and based at least on a type of job of a user and the user's level of exposure to email, one or more values representing a frequency at which the user is expected to receive a phishing communication and a propensity of the user to interact with the phishing communication;
determining, by the one or more processors, a risk score of the user based at least on a function of the one or more values, the risk score comprising a probability of the user to interact with the phishing communication; and
taking, by the one or more processors, an action based at least on the risk score of the user.

2. The method of claim 1 , further comprising taking, by the one or more processors, the action to display the risk score of the user.

3. The method of claim 2 , further comprising displaying the risk score of the user among a plurality of risk scores of a plurality of users.

4. The method of claim 1 , further comprising identifying, by the one or more processors, a severity value for a severity of the user's interaction with the phishing communication.

5. The method of claim 4 , further comprising determining, by the one or more processors, the risk score of the user based at least on the function of the one or more values and the severity value.

6. The method of claim 1 , further comprising determining, by the one or more processors, the risk score of the user by applying a weight to at least one value of the one or more values.

7. The method of claim 1 , further comprising determining, by the one or more processors, the one or more values based at least on a breach score value of the user.

8. The method of claim 7 , wherein the breach score value is based on the user's level of exposure to email.

9. The method of claim 1 , wherein the phishing communication is a malicious attack.

10. The method of claim 1 , wherein the phishing communication is a simulated phishing communication.

11. A system comprising:
one or more processors, coupled to memory and configured to:
identify, based at least on a type of job of a user and the user's level of exposure to email, one or more values representing a frequency at which the user is expected to receive a phishing communication and a propensity of the user to interact with the phishing communication;
determine a risk score of the user based at least on a function of the one or more values, the risk score comprising a probability of the user to interact with the phishing communication; and
taking an action based at least on the risk score of the user.

12. The system of claim 11 , wherein the one or more processors are further configured to take the action to display the risk score of the user.

13. The system of claim 12 , wherein the one or more processors are further configured to display the risk score of the user among a plurality of risk scores of a plurality of users.

14. The system of claim 11 , wherein the one or more processors are further configured to identify a severity value for a severity of the user's interaction with the phishing communication.

15. The system of claim 14 , wherein the one or more processors are further configured to determine the risk score of the user based at least on the function of the one or more values and the severity value.

16. The system of claim 11 , wherein the one or more processors are further configured to determine the risk score of the user by applying a weight to at least one value of the one or more values.

17. The system of claim 11 , wherein the one or more processors are further configured to determine the one or more values based at least on a breach score value of the user.

18. The system of claim 17 , wherein the breach score value is based on the user's level of exposure to email.

19. The system of claim 11 , wherein the phishing communication is a malicious attack.

20. The system of claim 11 , wherein the phishing communication is a simulated phishing communication.

Assignees

• Knowbe4 Inc

Inventors

• Sites Eric
• Kras Greg
• Irimie Alin
• Sjouwerman Stu
• Castilho Marcio
• Martens Siegfried
• Bonabeau Eric
• Kime Kristian

Classifications

• H04L63/1408 Primary

  by monitoring network traffic (monitoring network traffic per se H04L43/00) · CPC title

• H04L63/14

  for detecting or protecting against malicious traffic · CPC title

• G06F21/577

  Assessing vulnerabilities and evaluating computer system security · CPC title

• H04L63/1416 Primary

  Event detection, e.g. attack signature detection · CPC title

• H04L63/1433

  Vulnerability analysis · CPC title