Implementing user-specific local administrator rights using artificial intelligence techniques
An example computer-implemented method provided herein includes obtaining data pertaining to at least one request for local administrator rights (LAR) from a given user; determining one or more recommendations related to the at least one request for LAR by processing at least a portion of the obtained data using one or more artificial intelligence techniques; modifying at least a portion of the LAR associated with the at least one request to encompass at least a portion of the one or more recommendations; and automatically implementing the modified LAR with respect to one or more devices associated with the given user.
1 . A computer-implemented method comprising:
obtaining data pertaining to at least one request for local administrator rights (LAR) from a given user;
determining one or more recommendations related to the at least one request for LAR by processing at least a portion of the obtained data using one or more artificial intelligence techniques, wherein determining the one or more recommendations comprises identifying at least one of one or more software libraries and one or more software packages, related to the LAR associated with the at least one request, to be implemented in connection with the LAR;
modifying at least a portion of the LAR associated with the at least one request to encompass at least a portion of the one or more recommendations; and
automatically implementing the modified LAR with respect to one or more devices associated with the given user;
wherein the method is performed by at least one processing device comprising a processor coupled to a memory.
2 . The computer-implemented method of claim 1 , wherein determining the one or more recommendations comprises processing the at least a portion of the obtained data using at least one neural network-based matching engine to associate the at least one request for LAR with one or more software applications.
3 . The computer-implemented method of claim 2 , wherein processing the at least a portion of the obtained data using at least one neural network-based matching engine comprises processing the at least a portion of the obtained data using one or more pre-trained bidirectional encoder representations from transformers (BERT) models to generate contextual word embeddings to be used in connection with one or more approximate semantic name matching processes.
4 . The computer-implemented method of claim 3 , wherein using the contextual word embeddings in connection with one or more approximate semantic name matching processes comprises utilizing one or more fuzzy string matching distances metrics in connection with implementing at least one search mechanism to monitor whether the one or more software applications are utilized in connection with LAR related to the LAR associated with the at least one request.
5 . The computer-implemented method of claim 1 , wherein modifying the at least a portion of the LAR comprises incorporating one or more instructions pertaining to the at least a portion of the one or more recommendations.
6 . The computer-implemented method of claim 1 , wherein modifying the at least a portion of the LAR comprises restricting access, based at least in part on the at least a portion of the one or more recommendations, to one or more software applications within an original scope of the LAR.
7 . The computer-implemented method of claim 1 , wherein identifying the at least one of one or more software libraries and one or more software packages comprises performing one or more collaborative filtering techniques comprising creating combined vector representations of at least one of multiple software libraries and multiple software packages with respect to one or more software applications associated with the LAR.
8 . The computer-implemented method of claim 1 , wherein identifying the at least one of one or more software libraries and one or more software packages comprises identifying at least one of one or more approved software libraries and one or more approved packages used by one or more users, sharing one or more similarities with the given user, in association with at least one of one or more software applications associated with the LAR.
9 . The computer-implemented method of claim 1 , wherein obtaining the data pertaining to the at least one request for LAR comprises performing source attribute detection in connection with the at least one request for LAR.
10 . The computer-implemented method of claim 9 , wherein performing the source attribute detection comprises determining, by processing at least a portion of the obtained data pertaining to the at least one request for LAR using one or more command line utilities, one or more source attributes comprising at least one of enterprise name associated with the at least one request for LAR, file version associated with the at least one request for LAR, identifying information associated with the given user, product name associated with the at least one request for LAR, and product version associated with the at least one request for LAR.
11 . The computer-implemented method of claim 1 , further comprising:
performing one or more automated actions based at least in part on feedback related to the automatic implementation of the modified LAR.
12 . The computer-implemented method of claim 11 , wherein performing the one or more automated actions comprises automatically training at least a portion of the one or more artificial intelligence techniques using one or more portions of the feedback.
13 . A non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes the at least one processing device:
to obtain data pertaining to at least one request for local administrator rights (LAR) from a given user;
to determine one or more recommendations related to the at least one request for LAR by processing at least a portion of the obtained data using one or more artificial intelligence techniques, wherein determining the one or more recommendations comprises identifying at least one of one or more software libraries and one or more software packages, related to the LAR associated with the at least one request, to be implemented in connection with the LAR;
to modify at least a portion of the LAR associated with the at least one request to encompass at least a portion of the one or more recommendations; and
to automatically implement the modified LAR with respect to one or more devices associated with the given user.
14 . The non-transitory processor-readable storage medium of claim 13 , wherein determining the one or more recommendations comprises processing the at least a portion of the obtained data using at least one neural network-based matching engine to associate the at least one request for LAR with one or more software applications.
15 . The non-transitory processor-readable storage medium of claim 14 , wherein processing the at least a portion of the obtained data using at least one neural network-based matching engine comprises processing the at least a portion of the obtained data using one or more pre-trained bidirectional encoder representations from transformers (BERT) models to generate contextual word embeddings to be used in connection with one or more approximate semantic name matching processes.
16 . The non-transitory processor-readable storage medium of claim 13 , wherein modifying the at least a portion of the LAR comprises incorporating one or more instructions pertaining to the at least a portion of the one or more recommendations.
17 . An apparatus comprising:
at least one processing device comprising a processor coupled to a memory;
the at least one processing device being configured:
to obtain data pertaining to at least one request for local administrator rights (LAR) from a given user;
to determine one or more recommendations related to the at least one request for LAR by processing at least a portion of the obtained data using one or more artificial intelligence techniques, wherein determining the one or more recommendations comprises identifying at least one of one or more software libraries and one or more software packages, related to the LAR associated with the at least one request, to be implemented in connection with the LAR;
to modify at least a portion of the LAR associated with the at least one request to encompass at least a portion of the one or more recommendations; and
to automatically implement the modified LAR with respect to one or more devices associated with the given user.
18 . The apparatus of claim 17 , wherein determining the one or more recommendations comprises processing the at least a portion of the obtained data using at least one neural network-based matching engine to associate the at least one request for LAR with one or more software applications.
19 . The apparatus of claim 18 , wherein processing the at least a portion of the obtained data using at least one neural network-based matching engine comprises processing the at least a portion of the obtained data using one or more pre-trained bidirectional encoder representations from transformers (BERT) models to generate contextual word embeddings to be used in connection with one or more approximate semantic name matching processes.
20 . The apparatus of claim 17 , wherein modifying the at least a portion of the LAR comprises restricting access, based at least in part on the at least a portion of the one or more recommendations, to one or more software applications within an original scope of the LAR.