PATENT CLAIM ANALYSIS

Application Number: 15995073
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-10
Patent Classification: ["726", "023000"]

Abstract:
A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

Claim (Index 9):
The method of  claim 1 , wherein detecting the anomaly is further based on classification metadata for the particular user indicative of the particular user being at least one of a regular user, an administrative user, or an automated user.

Metadata:
- Claim Count in Document: 80.0
- Percentile: 93.0
- Lexical Diversity: 1.58667
- Patent Class: 726.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14929196', '14929037', '14929183', '14928421', '15418546']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3866896264986318
- 35 USC 102 Novelty (BERT): 0.5720709236494643
- Combined Prediction Score: 0.405227756213715
- Mean Citation Score: 435.45975800000014
- Max Citation Score: 508.20273
- Similarity Product: 371.9253954051268

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