Train a machine learning model using IP addresses and connection contexts
Abstract:
According to examples, an apparatus may include a processor and a non-transitory computer readable medium on which is stored machine readable instructions that may cause the processor to identify Internet protocol (IP) addresses and connection attributes associated with the IP addresses. The instructions may also cause the processor to train a machine learning model using the IP addresses as inputs to the machine learning model and connection contexts as outputs of the machine learning model. The machine learning model may learn a first weight matrix corresponding to the IP addresses and a second weight matrix corresponding to the connection contexts. In addition, the connection contexts may be concatenations of the connection attributes associated with a corresponding IP address.
Information query
Patent Agency Ranking
0/0