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 9):
The data processing method of  claim 8 , further comprising computing values i t , f t  and o t  as:\n forget gate:  f t =\u03c3( W f [ h t-1 ,x t ]+ b f ) input gate:  i t =\u03c3( W i [ h t-1 ,x t ]+ b i ) output gate:  o t =\u03c3( W o [ h t-1 ,x t ]+ b o ) wherein weights W and biases b are learned from training sequences.

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): 0.2246107738851404
- 35 USC 102 Novelty (BERT): 0.545313473063737
- Combined Prediction Score: 0.256681043803
- Mean Citation Score: 217.461342
- Max Citation Score: 385.92584
- Similarity Product: 351.1618385558557

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