PATENT CLAIM ANALYSIS

Application Number: 16215491
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-06
Patent Classification: ["726", "023000"]

Abstract:
Systems and methods for utilizing statistical relational learning techniques in order to predict factors for nodes of a node graph, such as a node graph that represents attacks and incidents to a computing system, are described. In some embodiments, the systems and methods identify certain nodes (of a node graph) as representing malicious attributes of an email or other threat artifact received by a computing system or network and utilize relational learning to predict the maliciousness of attributes represented by other nodes (of the node graph).

Claim (Index 18):
The method of  claim 11 , wherein generating node graphs for threat artifacts received by the computing system includes generating a node graph for a received phishing email that includes: (1) a node that represents an email, (2) a node that represents a sender of the email, (3) a node that represents a recipient of the email, and (4) a node that represents an attachment to the email.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 98.0
- Lexical Diversity: 1.72727
- Patent Class: 726.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15848337', '15236575', '15236595', '15236582', '16029964']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.278986130933258
- 35 USC 102 Novelty (BERT): 0.4784095769661631
- Combined Prediction Score: 0.2989284755365485
- Mean Citation Score: 148.58066000000005
- Max Citation Score: 151.89603
- Similarity Product: 103.42727095653892

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

Dataset: test