Data loss prevention on images

1. A non-transitory computer-readable storage medium having computer-readable code stored thereon for programming one or more processors to perform steps of:

detecting an image via a cloud-based system in monitored outbound user traffic, wherein a file is determined to be an image based on determining one of a file type, a specific set of bytes, and a file being not searchable for text;

scanning the image to identify any text and extracting any identified text therein;

responsive to the extracting, scanning the extracted text in the cloud-based system with a plurality of Data Loss Prevention (DLP) techniques including one or more DLP engines where the extracted text is checked to trigger the one or more DLP engines, Exact Data Matching (EDM) where the extracted text is matched to determine if it matches specific content, and Indexed Data Matching (IDM) where the extracted text is matched to some part of a document from a repository of documents, wherein at least one of the plurality of DLP engines includes a predefined dictionary and at least one of the plurality of DLP engines includes a custom dictionary;

obtaining expressions for the plurality of DLP engines, wherein the expressions include one or more DLP dictionaries that evaluate to a score for comparison with a corresponding threshold and one or more logical operators used to combine an evaluation of the one or more DLP dictionaries;

evaluating the image using the plurality of DLP engines and the expressions;

determining a DLP trigger based on a result of an expression that is a logical TRUE; and

performing one or more actions based on results of the plurality of DLP techniques.

2. The non-transitory computer-readable storage medium of claim 1 , wherein the steps further include

inline monitoring the user traffic with a cloud service.

3. The non-transitory computer-readable storage medium of claim 2 , wherein the detecting the image is performed selectively based on detecting the user traffic is associated with any of social media, electronic mail, and posts on Web sites.

4. The non-transitory computer-readable storage medium of claim 1 , wherein the plurality of DLP techniques include at least one DLP engine for detecting embarrassing content based on detecting the user traffic is associated with any of social media, electronic mail, and posts on Web sites.

5. The non-transitory computer-readable storage medium of claim 1 , wherein the plurality of DLP techniques include a plurality of the DLP engines that look for content matching one or more DLP dictionaries associated with the plurality of DLP engines.

6. The non-transitory computer-readable storage medium of claim 5 , wherein at least one of the plurality of DLP engines includes a predefined dictionary including adult content.

7. The non-transitory computer-readable storage medium of claim 1 , wherein the scanning the image to identify any text and extracting any identified text therein includes

detecting some text in the image via Optical Character Recognition; and

extracting the some text when the some text is above a similarity threshold amount associated with one or more categories.

8. The non-transitory computer-readable storage medium of claim 1 , wherein the one or more actions include any of blocking the image in a cloud service and providing a notification.

9. A method comprising:

detecting an image via a cloud-based system in monitored outbound user traffic, wherein a file is determined to be an image based on determining one of a file type, a specific set of bytes, and a file being not searchable for text;

scanning the image to identify any text and extracting any identified text therein;

responsive to the extracting, scanning the extracted text in the cloud-based system with a plurality of Data Loss Prevention (DLP) techniques including one or more DLP engines where the extracted text is checked to trigger the one or more DLP engines, Exact Data Matching (EDM) where the extracted text is matched to determine if it matches specific content, and Indexed Data Matching (IDM) where the extracted text is matched to some part of a document from a repository of documents, wherein at least one of the plurality of DLP engines includes a predefined dictionary and at least one of the plurality of DLP engines includes a custom dictionary;

obtaining expressions for the plurality of DLP engines, wherein the expressions include one or more DLP dictionaries that evaluate to a score for comparison with a corresponding threshold and one or more logical operators used to combine an evaluation of the one or more DLP dictionaries;

evaluating the image using the plurality of DLP engines and the expressions;

determining a DLP trigger based on a result of an expression that is a logical TRUE; and

performing one or more actions based on results of the plurality of DLP techniques.

10. The method of claim 9 , further comprising

inline monitoring the user traffic with a cloud service.

11. The method of claim 10 , wherein the detecting the image is performed selectively based on detecting the user traffic is associated with any of social media, electronic mail, and posts on Web sites.

12. The method of claim 9 , wherein the plurality of DLP techniques include at least one DLP engine for detecting embarrassing content based on detecting the user traffic is associated with any of social media, electronic mail, and posts on Web sites.

13. The method of claim 9 , wherein the plurality of DLP techniques include a plurality of the DLP engines that look for content matching one of more DLP dictionaries associated with the plurality of DLP engines.

14. The method of claim 13 , wherein at least one of the plurality of DLP engines includes a predefined dictionary including adult content.

15. The method of claim 9 , wherein the scanning the image to identify any text and extracting any identified text therein includes

detecting some text in the image via Optical Character Recognition; and

extracting the some text when the some text is above a similarity threshold amount associated with one or more categories.

16. The method of claim 9 , wherein the one or more actions include any of blocking the image in a cloud service and providing a notification.

17. A cloud-based system comprising:

a plurality of enforcement nodes connected to one another;

a plurality of processors communicatively coupled to the plurality of enforcement nodes;

a central authority connected to the plurality of enforcement nodes; and

memory storing instructions for a Data Loss Prevention (DLP) service executed between the plurality of enforcement nodes, wherein the DLP service is configured to

detect an image via the cloud-based system in monitored outbound user traffic, wherein a file is determined to be an image based on determining one of a file type, a specific set of bytes, and a file being not searchable for text;

scan the image to identify any text and extracting any identified text therein;

responsive to extraction of the identified text, scan the extracted text in the cloud-based system with a plurality of Data Loss Prevention (DLP) techniques including one or more DLP engines where the extracted text is checked to trigger the one or more DLP engines, Exact Data Matching (EDM) where the extracted text is matched to determine if it matches specific content, and Indexed Data Matching (IDM) where the extracted text is matched to some part of a document from a repository of documents, wherein at least one of the plurality of DLP engines includes a predefined dictionary and at least one of the plurality of DLP engines includes a custom dictionary;

obtaining expressions for the plurality of DLP engines, wherein the expressions include one or more DLP dictionaries that evaluate to a score for comparison with a corresponding threshold and one or more logical operators used to combine an evaluation of the one or more DLP dictionaries;

evaluating the image using the plurality of DLP engines and the expressions;

determining a DLP trigger based on a result of an expression that is a logical TRUE; and

perform one or more actions based on results of the plurality of DLP techniques.

18. The cloud-based system of claim 17 , wherein the DLP service is performed with an inline monitoring service through the cloud-based system.