PATENT CLAIM ANALYSIS

Application Number: 16161572
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-02
Patent Classification: ["726", "023000"]

Abstract:
A computer-implemented data processing method comprises: executing a recurrent neural network (RNN) comprising nodes each implemented as a Long Short-Term Memory (LSTM) cell and comprising links between nodes that represent outputs of LSTM cells and inputs to LSTM cells, wherein each LSTM cell implements an input layer, hidden layer and output layer of the RNN; receiving network traffic data associated with networked computers; extracting feature data representing features of the network traffic data and providing the feature data to the RNN; classifying individual Uniform Resource Locators (URLs) as malicious or legitimate using LSTM cells of the input layer, wherein inputs to the LSTM cells are individual characters of the URLs, and wherein the LSTM cells generate feature representation; based on the feature representation, generating signals to a firewall device specifying either admitting or denying the URLs.

Claim (Index 1):
A computer-implemented method comprising:\n executing, in computer memory, a recurrent neural network (RNN) comprising a plurality of nodes each implemented as a Long Short-Term Memory (LSTM) cell and comprising a plurality of links between nodes that represent outputs of LSTM cells and inputs to LSTM cells, wherein each LSTM cell implements an input layer, hidden layer and output layer of the RNN; receiving, from a networked computer, network traffic data associated with one or more networked computers; extracting feature data representing a plurality of features of the network traffic data and providing the feature data to the RNN; classifying one or more individual Uniform Resource Locators (URLs) as malicious or legitimate using a plurality of first LSTM cells of the input layer, wherein inputs to the first LSTM cells are individual characters of the one or more URL; receiving a feature representation as input, the feature representation being associated with a particular connection of a particular computer, classifying the feature representation as malicious or legitimate using the RNN and creating and storing a connection data item that specifies whether the particular connection is malicious or legitimate based upon the preceding classifying of the feature representation; based on the connection data item, generating signals to a firewall device specifying either admitting or denying the particular connection.

Metadata:
- Claim Count in Document: 4.0
- Percentile: 97.0
- Lexical Diversity: 1.88889
- Patent Class: 726.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15253659', '15821231', '15680584', '15429806', '15843953']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2249970772849284
- 35 USC 102 Novelty (BERT): 0.5448654703496835
- Combined Prediction Score: 0.2569839165914039
- Mean Citation Score: 217.461342
- Max Citation Score: 385.92584
- Similarity Product: 335.1519766510296

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test