Leveraging sentiment in data protection systems
Systems and methods for providing data protection operations including cyber-threat protection operations. A sentiment analysis may be performed using language analysis to identify or determine a general or specific sentiment with or without intent to do harm. A score of the sentiment is then determined to assess risk. The data backup policy can be updated based on the assessed risk.
1. A method for performing data protection for backup storage, the method comprising:
collecting data from a source;
parsing the collected data, wherein portions of the collected data associated with specific users are stored as time series data for each of the specific users;
performing a sentiment analysis on the collected data, wherein the sentiment analysis includes detecting changes in sentiments of the specific users based on the time series data;
performing an intent analysis on the collected data, wherein the intent analysis accounts for portions of the data that intensify a sentiment of the data;
scoring the collected data based on the sentiment analysis and the intent analysis with a score to determine a risk associated with the collected data, wherein the portions of the data that intensify the sentiment increase a score of the collected data; and
updating a backup policy associated with the backup storage based on the determined risk.
2. The method of claim 1 , further comprising collecting the data from forums, websites, or chatrooms in the darknet.
3. The method of claim 1 , wherein performing a sentiment analysis includes
performing a language analysis on the collected data.
4. The method of claim 3 , further comprising parsing the collected data into at least one document.
5. The method of claim 4 , further comprising determining a subject of the collected data.
6. The method of claim 3 , further comprising scoring the collected data based on the language analysis.
7. The method of claim 6 , further comprising scoring the collected data per user.
8. The method of claim 1 , wherein the determined risk indicates that a primary data storage system is at risk, further comprising completing backup of critical applications and stopping backup of non-critical applications.
9. The method of claim 1 , wherein the determined risk indicates that the backup storage is at risk, further comprising automatically stopping all backups and closing the backup device to all networking.
10. The method of claim 1 , wherein the determined risk indicates that the backup storage is at risk, further comprising locking data in a retention mode.
11. A non-transitory computer readable medium comprising computer executable instructions that, when executed, perform a method for performing data protection for backup storage, the method comprising:
collecting data from a source;
parsing the collected data, wherein portions of the collected data associated with specific users are stored as time series data for each of the specific users;
performing a sentiment analysis on the collected data, wherein the sentiment analysis includes detecting changes in sentiments of the specific users based on the time series data;
performing an intent analysis on the collected data, wherein the intent analysis accounts for portions of the data that intensify a sentiment of the data;
scoring the collected data based on the sentiment analysis and the intent analysis with a score to determine a risk associated with the collected data, wherein the portions of the data that intensify the sentiment increase a score of the collected data; and
updating a backup policy associated with the backup storage based on the determined risk.
12. The non-transitory computer readable medium of claim 11 , further comprising collecting the data from at least one of forums, websites, or chatrooms in the darknet or other network.
13. The non-transitory computer readable medium of claim 11 , wherein performing a sentiment analysis includes
performing a language analysis on the collected data.
14. The non-transitory computer readable medium of claim 13 , further comprising parsing the sentiment into at least one document.
15. The non-transitory computer readable medium of claim 14 , further comprising determining a subject of the sentiment and determining if the subject is associated with an industry or a specific entity.
16. The non-transitory computer readable medium of claim 15 , further comprising scoring the sentiment based on the language analysis and the subject.
17. The non-transitory computer readable medium of claim 11 , wherein the determined risk indicates that a primary data storage system is at risk, further comprising completing backup of critical applications and stopping backup of non-critical applications.
18. The non-transitory computer readable medium of claim 11 , wherein the determined risk indicates that the backup storage is at risk, further comprising automatically stopping all backups and closing the backup device to all networking.
19. The non-transitory computer readable medium of claim 11 , wherein the determined risk indicates that the backup storage is at risk, further comprising locking data in a retention mode.