PATENT CLAIM ANALYSIS

Application Number: 15899453
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-08
Patent Classification: ["726", "001000"]

Abstract:
Embodiments of the present invention generate network communication policies by applying machine learning to existing network communications, and without using information that labels such communications as healthy or unhealthy. The resulting policies may be used to validate communication between applications (or services) over a network.

Claim (Index 1):
A method performed by at least one computer processor executing computer program instructions stored in at least one non-transitory computer-readable medium, the method comprising:\n (A) for each of a plurality of communications over a network between applications executing on a plurality of computer systems, collecting and storing data about the plurality of communications, including, for each of the plurality of communications:\n data representing a source application of the communication; and \n data representing a destination application of the communication; \n data representing a local Internet Protocol (IP) address of the communication; and \n data representing a remote IP address of the communication; \n (B) obtaining flow data from the plurality of computer systems, wherein the flow data includes a plurality of flow objects, wherein each of the plurality of flow objects contains data representing communications involving a single corresponding application; (C) producing match data containing a plurality of match objects, wherein each of the match objects represents a pair of flow objects, in the plurality of flow objects, representing opposite ends of a network communication; and (D) generating a network communication model based on the match data.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 88.0
- Lexical Diversity: 1.19048
- Patent Class: 726.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15794111', '13842067', '13774879', '15786411', '13711094']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2500051847055299
- 35 USC 102 Novelty (BERT): 0.4728859362425897
- Combined Prediction Score: 0.2722932598592359
- Mean Citation Score: 112.0350052
- Max Citation Score: 115.44193
- Similarity Product: 79.31503683103679

Labels:
- Claim Label 101: 0
- Claim Label 102: 0
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test