Privacy policy rating system

1. A system comprising:

a processor;

a memory accessible to the processor and storing instructions that, when executed by the processor, cause the processor to perform operations including:

automatically determining, at a privacy policy analysis system (PPAS), a privacy policy score for a website based on an automatic semantic analysis of text of a privacy policy associated with the website;

receiving at the PPAS, from a user at a user device, user preferences that reflect a relative importance of at least one of one or more privacy policy characteristics to that user;

customizing, at the PPAS, the privacy policy score based on the user preferences of that user;

determining, at the PPAS, that the privacy policy score is below a threshold value;

blocking, at the user device, access to the website based on the privacy policy score falling below the threshold value;

detecting, at the PPAS, a change in the text of the privacy policy associated with the website after the privacy policy score is determined;

automatically determining, at the PPAS, an updated privacy policy score based on the change in the text of the privacy policy;

customizing, at the PPAS, the updated privacy policy score based on the user preferences of the user;

determining, at the PPAS, that the updated privacy policy score is not below the threshold value; and

unblocking, at the user device, access to the website based on the updated privacy policy score not being below the threshold value.

2. The system of claim 1 , further comprising instructions that cause the processor to perform operations including:

surveying a plurality of users for receiving, at the PPAS from the plurality of users, user preferences reflecting a relative importance of at least one of the one or more privacy policy characteristics to the plurality of users.

3. The system of claim 2 , wherein the user preferences received from the plurality of users are combined to produce a weighting factor for the one or more privacy policy characteristics, and wherein the weighting factor is used in determining the privacy policy score.

4. The system of claim 1 , further comprising instructions that cause the processor to perform operations including:

providing, at the PPAS, the privacy policy score to a privacy policy plugin associated with an Internet browser application executing on the user device.

5. The system of claim 4 , wherein blocking access to the website includes the privacy policy plugin blocking access to the website.

6. The system of claim 1 , wherein determining the privacy policy score for the website includes retrieving the privacy policy score from a database.

7. The system of claim 1 , wherein the detecting the change in the text of the privacy policy includes comparing the privacy policy with a stored privacy policy.

8. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium of a gateway device, including instructions configured to cause one or more data processors to perform operations including:

automatically determining, at a privacy policy analysis system (PPAS), a privacy policy score for a website based on an automatic semantic analysis of text of a privacy policy associated with the website;

receiving at the PPAS, from a user at a user device, user preferences that reflect a relative importance of at least one of one or more privacy policy characteristics to that user;

customizing, at the PPAS, the privacy policy score based on the user preferences of that user;

determining, at the PPAS, that the privacy policy score is below a threshold value;

blocking, at the user device, access to the website based on the privacy policy score falling below the threshold value;

detecting, at the PPAS, a change in the text of the privacy policy associated with the web site after the privacy policy score is determined;

automatically determining, at the PPAS, an updated privacy policy score based on the change in the text of the privacy policy;

customizing, at the PPAS, the updated privacy policy score based on the user preferences of the user;

determining, at the PPAS, that the updated privacy policy score is not below the threshold value; and

unblocking, at the user device, access to the website based on the updated privacy policy score not being below the threshold value.

9. The computer-program product of claim 8 , further comprising instructions configured to cause one or more data processors to perform operations including:

surveying a plurality of users for receiving, at the PPAS from the plurality of users, user preferences reflecting the relative importance of at least one of the one or more privacy policy characteristics to the plurality of users.

10. The computer-program product of claim 9 , wherein the user preferences received from the plurality of users are combined to produce a weighting factor for the one or more privacy policy characteristics, and wherein the weighting factor is used in determining the privacy policy score.

11. The computer-program product of claim 8 , further comprising instructions configured to cause one or more data processors to perform operations including:

providing, at the PPAS, the privacy policy score to a privacy policy plugin associated with an Internet browser application executing on the user device.

12. The computer-program product of claim 11 , wherein blocking access to the website includes the privacy policy plugin blocking access to the website.

13. The computer-program product of claim 8 , wherein determining the privacy policy score for the website includes retrieving the privacy policy score from a database.

14. The computer-program product of claim 8 , wherein the detecting the change in the text of the privacy policy includes comparing the privacy policy with a stored privacy policy.

15. A computer-implemented method, comprising:

automatically determining, at a privacy policy analysis system (PPAS), a privacy policy score for a website based on an automatic semantic analysis of text of a privacy policy associated with the website;

receiving at the PPAS, from a user at a user device, user preferences that reflect a relative importance of at least one of one or more privacy policy characteristics to that user;

customizing, at the PPAS, the privacy policy score based on the user preferences of that user;

determining, at the PPAS, that the privacy policy score is below a threshold value;

blocking, at the user device, access to the website based on the privacy policy score falling below the threshold value;

detecting, at the PPAS, a change in the text of the privacy policy associated with the website after the privacy policy score is determined;

automatically determining, at the PPAS, an updated privacy policy score based on the change in the text of the privacy policy;

customizing, at the PPAS, the updated privacy policy score based on the user preferences of the user;

determining, at the PPAS, that the updated privacy policy score is not below the threshold value; and

unblocking, at the user device, access to the website based on the updated privacy policy score not being below the threshold value.

16. The computer-implemented method of claim 15 , further comprising:

surveying a plurality of users for receiving, at the PPAS from the plurality of users, user preferences reflecting a relative importance of at least one of the one or more privacy policy characteristics to the plurality of users.

17. The computer-implemented method of claim 16 , wherein the user preferences received from the plurality of users are combined to produce a weighting factor for the one or more privacy policy characteristics, and wherein the weighting factor is used in determining the privacy policy score.

18. The computer-implemented method of claim 15 , further comprising:

providing, at the PPAS, the privacy policy score to a privacy policy plugin associated with an Internet browser application executing on the user device.

19. The computer-implemented method of claim 18 , wherein blocking access to the website includes the privacy policy plugin blocking access to the website.

20. The computer-implemented method of claim 15 , wherein the detecting the change in the text of the privacy policy includes comparing the privacy policy with a stored privacy policy.