PATENT CLAIM ANALYSIS

Application Number: 16242030
Application Type: Utility
Filing Date: 2019-01
Publication Date: 2019-05
Patent Classification: ["726", "023000"]

Abstract:
Methods and systems for classifying malicious locators. A processor is trained on a set of known malicious locators using a non-supervised learning procedure. Once trained, the processor may classify new locators as being generated by a particular generation kit.

Claim (Index 10):
A system for classifying malicious locators accessible through a network, the system comprising:\n an interface to a non-transitory computer-readable medium configured to access at least one locator that comprises the location of a malicious network-accessible resource; a network interface; and a processor in communication with the medium interface and the network interface, the processor configured to:\n extract at least one feature associated with the at least one locator; \n assign membership probabilities to the at least one locator based on the extracted at least one feature, wherein the membership probabilities each represent a probability the at least one locator belongs to a particular family of kits; and \n label the at least one locator as being generated by a kit with which the locator has the highest membership probability.

Metadata:
- Claim Count in Document: 9.0
- Percentile: 99.0
- Lexical Diversity: 1.26471
- Patent Class: 726.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15200530', '13742153', '15196072', '13726475', '15368349']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2594834581303965
- 35 USC 102 Novelty (BERT): 0.5304295803143152
- Combined Prediction Score: 0.2865780703487884
- Mean Citation Score: 208.492518
- Max Citation Score: 366.17862
- Similarity Product: 284.45852198119644

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