Method and system for translating natural language policy to logical access control policy

Abstract

Natural language policy text is translated into logical access control policy code with a policy composer that receives natural language policy text, an attribute dictionary connected to the policy composer to define attributes and their logical access control policy equivalents. A natural language policy set is connected to the policy composer and includes samples of natural language policy rules and their logical access control policy equivalents. The policy composer uses natural language processing, the attribute dictionary and the natural language policy set to translate the natural language policy text into logical access control code.

What is claimed: 
     
         1 . A system for translating natural language policy text into logical access control policy code, comprising:
 a policy composer to receive a sequence of free text natural language policy text strings provided by a user;   an attribute dictionary communicably connected to the policy composer defining attributes and their logical access control policy equivalents;   a natural language policy set communicably connected to the policy composer with samples of natural language policy rules and their logical access control policy equivalents;   wherein the policy composer is configured to use natural language processing to identify a plurality of candidate attributes in the sequence of free text natural language policy text strings and store the candidate attributes in the attribute dictionary; and   wherein the policy composer uses the attribute dictionary and the natural language policy set to translate the input natural language policy text strings into logical access control code.   
     
     
         2 . The system of  claim 1 , wherein the logical access control code is in XACML format. 
     
     
         3 . The system of  claim 1 , wherein the logical access control code is in NGAC format. 
     
     
         4 . The system of  claim 1 , wherein the attribute dictionary is populated with attributes from the natural language policy set. 
     
     
         5 . The system of  claim 1 , wherein the attribute dictionary is populated by user input. 
     
     
         6 . The system of  claim 1 , wherein the natural language processing comprises named entity recognition that identifies a named entity that is a string in the input free text natural language policy text strings, wherein a first natural language policy set includes metadata for the named entity from a previously translated policy. 
     
     
         7 . The system of  claim 1 , wherein the natural language processing comprises morphological segmentation. 
     
     
         8 . A method for translating natural language policy text into logical access control policy code, comprising:
 receiving a sequence of free text natural language policy text strings input by a user to a policy composer;   using natural language processing to identify a plurality of candidate attributes in the sequence of free text natural language policy text strings and store the candidate attributes in an attribute dictionary;   identifying a plurality of candidate natural language policy rules from a natural language policy set;   using the attribute dictionary and the natural language policy set to translate the input natural language policy text strings into logical access control code; and   storing the logical access control code in a policy archive.   
     
     
         9 . The method of  claim 8 , wherein the logical access control code is in XACML format. 
     
     
         10 . The method of  claim 8 , wherein the logical access control code is in NGAC format. 
     
     
         11 . The method of  claim 8 , wherein the attribute dictionary is populated with attributes from the natural language policy set. 
     
     
         12 . The method of  claim 8 , wherein the attribute dictionary is populated by user input. 
     
     
         13 . The method of  claim 8 , wherein the natural language processing comprises named entity recognition that identifies a named entity that is a string in the input free text natural language policy text strings, wherein a first natural language policy set includes metadata for the named entity from a previously translated policy. 
     
     
         14 . The method of  claim 8 , wherein the natural language processing comprises morphological segmentation. 
     
     
         15 . A non-transitory computer-readable medium comprising instructions for translating natural language policy text into logical access control policy code, the non-transitory computer-readable medium comprising instructions for:
 receiving a sequence of free text natural language policy text strings input by a user to a policy composer;   using natural language processing to identify a plurality of candidate attributes in the sequence of free text natural language policy text strings and store the candidate attributes in an attribute dictionary;   identifying a plurality of candidate natural language policy rules from a natural language policy set;   using the attribute dictionary and the natural language policy set to translate the input natural language policy text strings into logical access control code; and   storing the logical access control code in a policy archive.   
     
     
         16 . The non-transitory computer-readable medium of  claim 15 , wherein the logical access control code is in XACML format. 
     
     
         17 . The non-transitory computer-readable medium of  claim 15 , wherein the logical access control code is in NGAC format. 
     
     
         18 . The non-transitory computer-readable medium of  claim 15 , wherein the attribute dictionary is populated with attributes from the natural language policy set. 
     
     
         19 . The non-transitory computer-readable medium of  claim 15 , wherein the attribute dictionary is populated by user input. 
     
     
         20 . The non-transitory computer-readable medium of  claim 15 , wherein the natural language processing comprises named entity recognition that identifies a named entity that is a string in the input free text natural language policy text strings, wherein a first natural language policy set includes metadata for the named entity from a previously translated policy.