Apparatus and method for implementing a recommended cyber-attack security action
View Patent ↗An apparatus and method for determining a recommended cyber-attack security action are provided. The apparatus includes a processor and a memory communicatively coupled to the at least a processor. The memory contains instructions configuring the at least a processor to receive a cyber profile associated with a digital environment. The processor is further configured to receive a risk profile associated with the cyber profile and determine at least one security action based on the risk profile. In addition, the processor is configured to generating a user interface data structure configured to display the determined at least one security action.
1. An apparatus for implementing a cyber-attack security action, the apparatus comprising:
at least a processor; and
a memory communicatively coupled to the at least a processor, the memory containing instructions configuring the at least a processor to:
receive a cyber profile associated with a digital environment;
receive a risk profile associated with the cyber profile;
determine a plurality of security actions to be implemented in the digital environment based on the cyber profile and the risk profile, wherein the risk profile includes a single point of failure data;
determine a highest priority security action of the plurality of security actions by optimization of an objective function, wherein optimizing the objective function comprises minimizing the objective function as a function of time available for implementation of at least a security action of the plurality of security actions;
implement the highest priority security action in the digital environment; and
generate a user interface data structure configured to display the implemented security action on a user interface.
2. The apparatus of claim 1 , wherein the cyber profile comprises digital asset profile data, user data, and protective asset data associated with the digital environment.
3. The apparatus of claim 1 , wherein the risk profile comprises cyber-attack protection data, degree of single points of failure data, cyber-attack recovery protocol data, and a digital environment risk record.
4. The apparatus of claim 1 , wherein implementing the highest priority security action further comprises:
receiving security action training data comprising a plurality of risk profile data correlated to a plurality of security action data;
training a security action machine learning model as a function of the security action training data;
determining the highest priority security action using the security action machine learning model; and
implementing the highest priority security action determined by the security action machine learning model.
5. The apparatus of claim 4 , wherein the security action machine learning model is configured to determine a cyber profile category security action for each category of the cyber profile.
6. The apparatus of claim 5 , wherein the memory contains further instructions configuring the at least a processor to receive, by the user interface, a user selection of the cyber profile category security action to be implemented.
7. The apparatus of claim 4 , wherein the security action machine learning model is configured to determine a risk profile category security action for each category of the risk profile.
8. The apparatus of claim 7 , wherein the memory contains further instructions configuring the at least a processor to receive, by the user interface, a user selection of the risk profile category security action to be implemented.
9. The apparatus of claim 1 , wherein the memory contains further instructions configuring the at least a processor to receive, by the user interface, a user selection of the at least one security action to be implemented.
10. The apparatus of claim 1 , wherein the memory contains further instructions configuring the at least a processor to:
receive at least one digital environment constraint from a user via the user interface; and
modify the highest priority security action based on the at least one digital environment constraint.
11. A method for implementing a cyber-attack security action, the method comprising:
receiving, by a processor, a cyber profile associated with a digital environment;
receiving, by the processor, a risk profile associated with the cyber profile;
determining, by the processor, a plurality of security actions to be implemented in the digital environment based on the cyber profile and the risk profile, wherein the risk profile includes a single point of failure data;
determining, by the processor, a highest priority security action of the plurality of security actions by optimization of an objective function, wherein optimizing the objective function comprises minimizing the objective function as a function of time available for implementation of at least a security action of the plurality of security actions;
implementing, by the processor, the highest priority security action in the digital environment; and
generating, by the processor, a user interface data structure configured to display the implemented security action on a user interface.
12. The method of claim 11 , wherein the cyber profile comprises digital asset profile data, user data, and protective asset data associated with the digital environment.
13. The method of claim 11 , wherein the risk profile comprises cyber-attack protection data, degree of single points of failure data, cyber-attack recovery protocol data, and a digital environment risk record.
14. The method of claim 11 , wherein implementing the highest priority security action further comprises:
receiving, by the processor, security action training data comprising a plurality of risk profile data correlated to a plurality of security action data;
training, by the processor, a security action machine learning model as a function of the security action training data;
determining, by the processor, the highest priority security action using the security action machine learning model; and
implementing, by the processor, the highest priority security action determined by the security action machine learning model.
15. The method of claim 14 , further comprising determining, by the security action machine learning model, a cyber profile category security action for each category of the cyber profile.
16. The method of claim 15 , further comprising receiving, by the user interface, a user selection of the cyber profile category security action to be implemented.
17. The method of claim 14 , further comprising determining, by the security action machine learning model, a risk profile category security action for each category of the risk profile.
18. The method of claim 17 , further comprising receiving, by the user interface, a user selection of the risk profile category security action to be implemented.
19. The method of claim 11 , further comprising receiving, by the user interface, a user selection of at least one security action to be implemented.
20. The method of clam 11 , wherein the method further comprises:
receiving, by the processor, at least one digital environment constraint from a user via the user interface; and
modifying, by the processor, the highest priority security action based on the at least one digital environment constraint.