PATENT CLAIM ANALYSIS

Application Number: 16195322
Application Type: Utility
Filing Date: 2018-11
Publication Date: 2019-03
Patent Classification: ["434", "016000"]

Abstract:
A mission-based cyber training platform allows both offensive and defensive oriented participants to test their skills in a game-based virtual environment against a live or virtual opponent. The system builds realistic virtual environments to perform the training in an isolated and controlled setting. Dynamic configuration supports unique missions using a combination of real and/or virtual machines, software resources, tools, and network components. Game engine behaves in a manner that will vary if participant attempts to replay a scenario based upon alternate options available to the engine. Scoring and leader boards are used to identify skill gaps/strengths and measure performance for each training participant. A detailed assessment of a player's performance is provided at the end of the mission and is stored in a user profile/training record.

Claim (Index 16):
The system in accordance with  claim 15  wherein said system checks whether said student meets said set of core student competencies by presenting a test to said student at said student station or comparing said set of core student competencies to a stored student profile that includes information related to said set of core student competencies.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 98.0
- Lexical Diversity: 1.41667
- Patent Class: 434.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15466833', '15274096', '16056892', '16109430', '15498307']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.454323737137762
- 35 USC 102 Novelty (BERT): 0.6060691737567453
- Combined Prediction Score: 0.4694982807996603
- Mean Citation Score: 468.865508
- Max Citation Score: 607.4976
- Similarity Product: 495.1308561813355

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