PATENT CLAIM ANALYSIS

Application Number: 15952626
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2018-10
Patent Classification: ["702", "108000"]

Abstract:
A system and method for selecting a test vector for use in classification of electronic components. The system and method can quickly and automatically select a test vector that, when applied to a set of training electronic components, causes the electronic components to produce side channel information that can be used to build a classifier that accurately classifies a set of test electronic components.

Claim (Index 15):
An automated system for selecting a trained test vector set comprising:\n an electronic component interface configured for installation of a plurality of training components, wherein the electronic component interface is configured to apply a set of one or more training test vectors to the plurality of training components; a sensor configured to sense side channel information from each of the plurality of training components in response to the application of the one or more training test vectors to the training components via the electronic component interface; a control system configured to:\n create a classifier for each of the one or more training test vectors based on the side channel information sensed from each of the plurality of training components in response to the application of that training test vector; \n classify each of the plurality of training components with the classifier; \n determine a quality factor of each classifier; \n a machine learning module configured to update the set of one or more training test vectors based on the one or more training test vectors and the quality of each classifier created with those training test vectors; and wherein the automated system is configured to determine a trained test vector set based on the one or more training test vectors and the quality factor of each classifier.

Metadata:
- Claim Count in Document: 56.0
- Percentile: 91.0
- Lexical Diversity: 1.7
- Patent Class: 702.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15696667', '15178708', '12890789', '15223283', '15473980']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2006034578370436
- 35 USC 102 Novelty (BERT): 0.4822522976463378
- Combined Prediction Score: 0.228768341817973
- Mean Citation Score: 204.446454
- Max Citation Score: 229.14627
- Similarity Product: 181.39319550251125

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

Dataset: test