Systems, methods, and storage media for calculating the frequency of cyber risk loss within computing systems
Systems, methods, and storage media for determining the probability of cyber risk-related loss within one or more computing systems composed of computing elements are disclosed. Exemplary implementations may: assess vulnerability by determining an exposure window for a computing element based on the number of discrete times within a given time frame where the computing element is in a vulnerable state; determine a frequency of contact of the computing element with threat actors; normalize the exposure window and the frequency of contact; calculate a threat event frequency by dividing the normalized exposure window by the normalized frequency of contact; and repeat the steps for multiple elements. When combined with liability data that describes the loss magnitude implications of these events, organizations can prioritize the elements based on loss exposure and take action to prevent loss exposure.
1. A system configured for determining the frequency of cyber risk losses within one or more computing systems composed of computing elements, the system comprising:
one or more hardware processors configured by machine-readable instructions to:
assess vulnerability by determining an exposure window fora computing element based on the number of discrete times within a given time frame where the computing element is in a vulnerable state;
determine a frequency of contact of the computing element with threat actors:
normalize the exposure window and the frequency of contact;
wherein the normalizing of the exposure window is accomplished as part of assessing vulnerability and comprises setting the discrete time to a day and setting the given time frame to one year and the normalizing of the frequency of contact is accomplished as part of determining a frequency, by determining a mean time between contact that is represented byte number of days in a year by the number of contacts in a year;
calculate a loss event frequency by dividing the normalized exposure window by the normalized frequency of contact; and
repeat the operations above for multiple elements.
2. The system of claim 1 , wherein the exposure window, the frequency of contact and the loss event frequency are expressed as a range and the calculating loss event frequency includes applying a stochastic process.
3. The system of claim 1 , wherein assessing vulnerability comprises determining between exploitable vulnerable states and non-exploitable vulnerable states and using only exploitable vulnerable states in determining the number of discrete times.
4. The system of claim 1 , wherein determining a frequency comprises determining the position of the element within a threat landscape and wherein data indicating the frequency of contact is determined based on the position.
5. The system of claim 1 , wherein assessing vulnerability comprises using zero-day exploit information to determine the exposure window.
6. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to take cyber risk prevention activities based on the prioritization of elements.
7. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to combine the determined loss event frequency with loss magnitude data and prioritize elements based on loss exposure.
8. A method for prioritizing cyber risks within one or more computing systems composed of computing elements, the method comprising:
assessing vulnerability by determining an exposure window fora computing element based on the number of discrete times within a given time frame where the computing element is in a vulnerable state;
determining a frequency of contact of the computing element with threat actors;
normalizing the exposure window and the frequency of contact;
wherein the normalizing of the exposure window is accomplished as part of assessing vulnerability and comprises setting the discrete time to a day and setting the given time frame to one year and the normalizing of the frequency of contact is accomplished as part of determining a frequency, by determining a mean time between contact that is represented by the number of days in a year by the number of contacts in a year;
calculating a loss event frequency by dividing the normalized exposure window by the normalized frequency of contact; and
repeating the steps above for multiple elements.
9. The method of claim 8 , wherein the exposure window, the frequency of contact and the loss event frequency are expressed as a range and the calculating loss event frequency includes applying a stochastic process.
10. The method of claim 8 , wherein assessing vulnerability comprises determining between exploitable vulnerable states and non-exploitable vulnerable states and using only exploitable vulnerable states in determining the number of discrete times.
11. The method of claim 8 , wherein determining a frequency comprises determining the position of the element within a threat landscape and wherein data indicating the frequency of contact is determined based on the position.
12. The method of claim 8 , wherein assessing vulnerability comprises using zero-day exploit information to determine the exposure window.
13. The method of claim 8 , further comprising, taking cyber risk prevention activities based on the prioritization of elements.
14. The method of claim 8 , further comprising combining the determined loss event frequency with loss magnitude data and prioritizing elements based on loss exposure.
15. A non-transient computer-readable storage medium having instructions embodied thereon, the instructions being executable by one or more processors to perform a method for prioritizing cyber risks within one or more computing systems composed of computing elements, the method comprising:
assessing vulnerability by determining an exposure window fora computing element based on the number of discrete times within a given time frame where the computing element is in a vulnerable state;
determining a frequency of contact of the computing element with threat actors;
normalizing the exposure window and the frequency of contact;
wherein the normalizing of the exposure window is accomplished as part of assessing vulnerability and comprises setting the discrete time to a day and setting the given time frame to one year and the normalizing of the frequency of contact is accomplished as part of determining a frequency, by determining a mean time between contact that is represented by the number of days in a year by the number of contacts in a year;
calculating a loss event frequency by dividing the normalized exposure window by the normalized frequency of contact; and
repeating the operations above for multiple elements.
16. The computer-readable storage medium of claim 15 , wherein the exposure window, the frequency of contact and the loss event frequency are expressed as a range and the calculating loss event frequency includes applying a stochastic process.
17. The computer-readable storage medium of claim 15 , wherein assessing vulnerability comprises determining between exploitable vulnerable states and non-exploitable vulnerable states and using only exploitable vulnerable states in determining the number of discrete times.
18. The computer-readable storage medium of claim 15 , wherein determining a frequency comprises determining the position of the element within a threat landscape and wherein data indicating the frequency of contact is determined based on the position.
19. The computer-readable storage medium of claim 15 , wherein assessing vulnerability comprises using zero-day exploit information to determine the exposure window.
20. The computer-readable storage medium of claim 15 , wherein the method further comprises, taking cyber risk prevention activities based on the prioritization of elements.
21. The computer-readable storage medium of claim 15 , wherein the method further comprises combining the determined loss event frequency with loss magnitude data and prioritizing elements based on loss exposure.