Intelligent conversion of internet domain names to vector embeddings
AssigneeHughes Network Systems, LLC
InventorAmit Arora
Life of this patent
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Abstract
A method of and system for converting domain names to a vector space embedding may include receiving data relating to internet traffic over a network, organizing the data into one or more documents that make up a training dataset, each of the one or more documents including one or more Domain Name Server (DNS) queries, providing the training dataset to a deep neural network to generate at least one vector space embedding for one or more domain names, and providing the vector space embedding as an output.
Claims20
A data processing system comprising:
- a processor;
- and
- a memory in communication with the processor, the memory storing executable instructions that, when executed by the processor, cause the data processing system to perform functions of:
- receiving data relating to internet traffic over a network;
- organizing the data into one or more documents that make up a training dataset, each of the one or more documents including one or more Domain Name Server (DNS) queries;
- using the training dataset to generate at least one vector space embedding for one or more domain names;
- and
- providing the at least one vector space embedding as an output,
- wherein organizing the data into the one or more documents includes:
- sorting the one or more DNS queries in at least one of the one or more documents based on a frequency of occurrence of each of the one or more DNS queries, and
- removing a predetermined number of the one or more DNS queries having one or more highest frequencies of occurrence from the at least one of the one or more documents, the predetermined number of the one or more DNS queries representing one or more most frequently queried domain names within the one or more documents.
A method for converting domain names to a vector space embedding, the method comprising:
- receiving data relating to internet traffic over a network;
- organizing the data into one or more documents that make up a training dataset, each of the one or more documents including one or more Domain Name Server (DNS) queries;
- using the training dataset to generate at least one vector space embedding for one or more domain names;
- and
- providing the at least one vector space embedding as an output,
- wherein organizing the data into the one or more documents includes:
- sorting the one or more DNS queries in at least one of the one or more documents based on a frequency of occurrence of each of the one or more DNS queries, and
- removing a predetermined number of the one or more DNS queries having one or more highest frequencies of occurrence from the at least one of the one or more documents, the predetermined number of the one or more DNS queries representing one or more most frequently queried domain names within the one or more documents.
A non-transitory computer readable medium on which are stored instructions that when executed cause a programmable device to:
- receive data relating to internet traffic over a network;
- organize the data into one or more documents that make up a training dataset, each of the one or more documents including one or more Domain Name Server (DNS) queries;
- using the training dataset to generate at least one vector space embedding for one or more domain name;
- and
- provide the at least one vector space embedding as an output,
- wherein organizing the data into the one or more documents includes:
- sorting the one or more DNS queries in at least one of the one or more documents based on a frequency of occurrence of each of the one or more DNS queries, and
- removing a predetermined number of the one or more DNS queries having one or more highest frequencies of occurrence from the at least one of the one or more documents, the predetermined number of the one or more DNS queries representing one or more most frequently queried accessed domain names within the one or more documents.
Dependencies are inferred from the claim text.