SYSTEMS AND METHODS FOR EVALUATING A SEQUENCE OF CHARACTERS

• US 20100114560A1
• Filed: 11/05/2008
• Published: 05/06/2010
• Est. Priority Date: 11/05/2008
• Status: Active Grant

• Current Assignee: Citrix Systems, Inc. (Cloud Software Group)
• Original Assignee: Citrix Systems, Inc. (Cloud Software Group)
• Inventors: Spataro, Anthony
• Granted Patent: US 8,386,238 B2
• Time in Patent Office: Days
• US Class Current: 704/9
• CPC Class Codes: G06F 21/46 by designing passwords or checking the strength of passwords
• CPC Class Codes: G06F 40/284 Lexical analysis, e.g. tokenisation or collocates

Abstract

A sequence of characters may be evaluated to determine the presence of a natural language word. The sequence of characters may be analyzed to find a subsequence of alphabetical characters. Based on a statistical model of a natural language, a probability that the subsequence is a natural language word may be calculated. The probability may then be used to determine if the subsequence is indeed a natural language word.

Claims

1. A method of evaluating a sequence of characters to determine the presence of a natural language word in the sequence, the method comprising:

finding a subsequence of alphabetical characters in the sequence of characters;

calculating a probability that the subsequence is a natural language word using a statistical model of a natural language; and

determining if the subsequence is a natural language word based on the probability.

2. The method of claim 1, wherein the natural language is English.

3. The method of claim 1, wherein the statistical model is a Markov model.

4. The method of claim 3, wherein the Markov model models the orthography of the natural language.

5. The method of claim 3, wherein the Markov model records the probability that a particular character follows a given sequence of characters.

6. The method of claim 1, wherein calculating the probability comprises using Bayesian inference.

7. The method of claim 1, wherein the sequence of characters is a potential password.

8. The method of claim 7 further comprising evaluating the strength of the password.

9. The method of claim 8 further comprising outputting a Boolean answer reflecting the strength of the password.

10. The method of claim 8 further comprising outputting a numerical representation reflecting the strength of the password.

11. The method of claim 1, wherein finding a subsequence comprises searching the sequence of characters for a subsequence of alphabetic characters occurring between non-alphabetic characters.

12. The method of claim 1 further comprising iteratively performing the method of claim 1 for a plurality of subsequences in the sequence of characters.

13. The method of claim 1, wherein the sequence of characters is provided by a user and determining if the subsequence is a natural language word is performed in real-time after each character is input.

14. The method of claim 1, wherein the natural language word is selected from a specialized lexicon.

15. A system for evaluating a sequence of characters to determine the presence of a natural language word in the sequence, the system comprising:

a data store containing a statistical model of a natural language;

a search module for finding a subsequence of alphabetical characters in the sequence of characters;

a computation module for calculating a probability, based on the statistical model, that the subsequence of alphabetical characters is a natural language word, the computation module in communication with the data store and the search module; and

an evaluation module for determining if the subsequence is a natural language word based on the probability, the evaluation module in communication with the computation module.

16. The system of claim 15, wherein the system executes in a self-contained computing environment.

17. The system of claim 15 further comprising an input for receiving the sequence of characters.

18. The system of claim 15, wherein the system is a device with resource-constrained memory capacity.

19. The system of claim 15, wherein the system is a device with resource-constrained processing power.

20. The system of claim 15, wherein the system is selected from the group consisting of a cell phone, a personal digital assistant, a portable music player, and a web browser.

21. The system of claim 15, wherein the statistical model is a Markov model.

22. The system of claim 21, wherein the Markov model models the orthography of the natural language.

23. The system of claim 21, wherein the Markov model records the probability that a particular character follows a given sequence of characters.

24. The system of claim 15, wherein the computation module employs a Bayesian inference in calculating the probability.

25. The system of claim 15, wherein the sequence of characters is a potential password.