Protecting data based on a sensitivity level for the data

1. A computer-implemented method, comprising:

training a cognitive network, utilizing metadata associated with historic data threats;

inputting metadata associated with a malicious current data threat into the trained cognitive network, the metadata including an identification of the malicious current data threat, one or more types of data susceptible to and negatively affected by the malicious current data threat, and one or more locations where the malicious current data threat has occurred;

identifying, by the trained cognitive network, one or more stored instances of data determined to be vulnerable to the malicious current data threat,

wherein the one or more stored instances of data are susceptible to being attacked by the malicious current data threat; and

adjusting one or more security aspects of the one or more stored instances of data determined to be vulnerable to the malicious current data threat, wherein the adjusting includes backing up the one or more stored instances of data determined to be vulnerable to the malicious current data threat according to determined sensitivity level(s) of the one or more stored instances of data.

2. The computer-implemented method of claim 1 , wherein the cognitive network includes a neural network.

3. The computer-implemented method of claim 1 , wherein the historic data threats include instances of malware attacks, and the metadata associated with the historic data threats includes an identification of the historic data threats, one or more types of data susceptible to and negatively affected by the historic data threats, and one or more locations where the historic data threats have occurred.

4. The computer-implemented method of claim 1 , wherein the metadata associated with the historic data threats includes one or more types of data susceptible to the historic data threats.

5. The computer-implemented method of claim 1 , wherein the metadata associated with the historic data threats includes one or more locations where the historic data threats have occurred.

6. The computer-implemented method of claim 1 , wherein metadata associated with the one or more stored instances of data determined to be vulnerable to the historic data threats are labeled as vulnerable to the historic data threats, and are input into the cognitive network along with metadata associated with the historic data threats.

7. The computer-implemented method of claim 1 , wherein the malicious current data threat includes a malware attack, and the metadata associated with the malicious current data threat is extracted from one or more data sources.

8. The computer-implemented method of claim 1 , wherein the metadata associated with the malicious current data threat is extracted from one or more news sources, one or more blog posts, and one or more social media posts.

9. The computer-implemented method of claim 1 , wherein the trained cognitive network takes the metadata associated with the malicious current data threat as input, and outputs an indication of the one or more stored instances of data determined to be vulnerable to the malicious current data threat.

10. The computer-implemented method of claim 1 , wherein the one or more security aspects of the one or more stored instances of data determined to be vulnerable to the malicious current data threat are adjusted by changing a sensitivity level for the one or more stored instances of data.

11. The computer-implemented method of claim 1 , wherein the metadata associated with historic data threats includes:

an identification of the historic data threats,

one or more locations where the historic data threats have occurred,

a name of stored instances of data determined to be vulnerable to the historic data threats,

an owner of the stored instances of data determined to be vulnerable to the historic data threats,

a file size of the stored instances of data determined to be vulnerable to the historic data threats,

a platform in which the stored instances of data determined to be vulnerable to the historic data threats is utilized,

a last update time for the stored instances of data determined to be vulnerable to the historic data threats,

one or more topics associated with the stored instances of data determined to be vulnerable to the historic data threats,

one or more keywords found within the stored instances of data determined to be vulnerable to the historic data threats, and

one or more objects identified within the stored instances of data determined to be vulnerable to the historic data threats.

12. A computer program product comprising one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions comprising instructions configured to cause one or more processors to perform a method comprising:

training, by the one or more processors, a cognitive network, utilizing metadata associated with historic data threats;

inputting, by the one or more processors, metadata associated with a malicious current data threat into the trained cognitive network, the metadata including an identification of the malicious current data threat, one or more types of data susceptible to and negatively affected by the malicious current data threat, and one or more locations where the malicious current data threat has occurred;

identifying, by the one or more processors and the trained cognitive network, one or more stored instances of data determined to be vulnerable to the malicious current data threat; and

adjusting, by the one or more processors, one or more security aspects of the one or more stored instances of data determined to be vulnerable to the malicious current data threat, wherein the adjusting includes backing up the one or more stored instances of data determined to be vulnerable to the malicious current data threat according to determined sensitivity level(s) of the one or more stored instances of data.

13. The computer program product of claim 12 , wherein the cognitive network includes a neural network.

14. The computer program product of claim 12 , wherein the metadata associated with the historic data threats includes an identification of the historic data threats.

15. The computer program product of claim 12 , wherein the metadata associated with the historic data threats includes one or more types of data susceptible to the historic data threats.

16. The computer program product of claim 12 , wherein metadata associated with the one or more stored instances of data determined to be vulnerable to the historic data threats are labeled as vulnerable to the historic data threats, and are input into the cognitive network along with metadata associated with the historic data threats.

17. The computer program product of claim 12 , wherein the metadata associated with the malicious current data threat is extracted from one or more data sources.

18. The computer program product of claim 12 , wherein the metadata associated with the malicious current data threat is extracted from one or more news sources, one or more blog posts, and one or more social media posts, and the program instructions comprising instructions configured to cause the one or more processors to perform the method comprising: determining, by the one or more processors, the sensitivity level(s) of the one or more stored instances of data.

19. The computer program product of claim 12 , wherein the trained cognitive network takes the metadata associated with the malicious current data threat as input, and outputs an indication of the one or more stored instances of data determined to be vulnerable to the malicious current data threat.

20. A system, comprising:

a processor; and

logic integrated with the processor, executable by the processor, or integrated with and executable by the processor, the logic being configured to:

train a cognitive network, utilizing metadata associated with historic data threats;

input metadata associated with a malicious current data threat into the trained cognitive network, the metadata including an identification of the malicious current data threat, one or more types of data susceptible to and negatively affected by the malicious current data threat, and one or more locations where the malicious current data threat has occurred;

identify, by the trained cognitive network, one or more stored instances of data determined to be vulnerable to the malicious current data threat; and

backing up, by the trained cognitive network, the one or more stored instances of data determined to be vulnerable to the malicious current data threat, wherein data determined to be vulnerable to the malicious current data threat and to have a higher level of sensitivity is backed up at a higher frequency than data determined to be vulnerable to the malicious current data threat and to have a lower level of sensitivity.

21. The system of claim 20 , wherein the metadata includes: an identification of the malicious current data threat, one or more types of data susceptible to and negatively affected by the malicious current data threat, and one or more locations where the malicious current data threat has occurred.

22. A computer-implemented method, comprising:

training a cognitive network, including providing, as input into the cognitive network, metadata associated with an historic data threat, including:

an identification of the historic data threat,

one or more locations where the historic data threat has occurred,

a name of a stored instance of data determined to be vulnerable to the historic data threat,

an owner of the stored instance of data determined to be vulnerable to the historic data threat,

a file size of the stored instance of data determined to be vulnerable to the historic data threat,

a platform in which the stored instance of data determined to be vulnerable to the historic data threat is utilized,

a last update time for the stored instance of data determined to be vulnerable to the historic data threat,

one or more topics associated with the stored instance of data determined to be vulnerable to the historic data threat,

one or more keywords found within the stored instance of data determined to be vulnerable to the historic data threat, and

one or more objects identified within the stored instance of data determined to be vulnerable to the historic data threat;

inputting into the trained cognitive network, metadata associated with a current data threat, including:

an identification of the current data threat,

one or more types of data susceptible to and negatively affected by the current data threat, and

one or more locations where the current data threat has occurred;

identifying, by the trained cognitive network, metadata determined to be vulnerable to the current data threat;

comparing the metadata determined to be vulnerable to the current data threat to metadata associated with one or more stored instances of data to determine one or more stored instances of data determined to be vulnerable to the current data threat; and

adjusting one or more security aspects of the one or more stored instances of data determined to be vulnerable to the current data threat.

23. The computer-implemented method of claim 22 , wherein adjusting one or more security aspects of the one or more stored instances of data determined to be vulnerable to the current data threat includes immediately backing up one or more stored instances of data determined to be vulnerable to the current data threat.

24. The computer-implemented method of claim 22 , wherein adjusting one or more security aspects of the one or more stored instances of data determined to be vulnerable to the current data threat includes changing a sensitivity level for the one or more stored instances of data determined to be vulnerable to the current data threat.

25. A computer program product comprising one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions comprising instructions configured to cause one or more processors to perform a method comprising:

training, by the one or more processors, a cognitive network, including providing, as input into the cognitive network, metadata associated with an historic data threat, including:

an identification of the historic data threat,

one or more locations where the historic data threat has occurred,

a name of a stored instance of data determined to be vulnerable to the historic data threat,

an owner of the stored instance of data determined to be vulnerable to the historic data threat,

a file size of the stored instance of data determined to be vulnerable to the historic data threat,

a platform in which the stored instance of data determined to be vulnerable to the historic data threat is utilized,

a last update time for the stored instance of data determined to be vulnerable to the historic data threat,

one or more topics associated with the stored instance of data determined to be vulnerable to the historic data threat,

one or more keywords found within the stored instance of data determined to be vulnerable to the historic data threat, and

one or more objects identified within the stored instance of data determined to be vulnerable to the historic data threat;

inputting into the trained cognitive network, by the one or more processors, metadata associated with a current data threat, including:

an identification of the current data threat,

one or more types of data susceptible to and negatively affected by the current data threat, and

one or more locations where the current data threat has occurred;

identifying, by the one or more processors and the trained cognitive network, metadata determined to be vulnerable to the current data threat;

comparing, by the one or more processors, the metadata determined to be vulnerable to the current data threat to metadata associated with one or more stored instances of data to determine one or more stored instances of data determined to be vulnerable to the current data threat; and

adjusting, by the one or more processors, one or more security aspects of the one or more stored instances of data determined to be vulnerable to the current data threat.