PATENT CLAIM ANALYSIS

Application Number: 16008374
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-10
Patent Classification: ["726", "024000"]

Abstract:
Disclosed are devices, systems, apparatus, methods, products, media and other implementations, including a method that includes obtaining hardware-based micro-architectural data, including hardware-based micro-architectural counter data, for a hardware device executing one or more processes, and determining based, at least in part, on the hardware-based micro-architectural data whether at least one of the one or more processes executing on the hardware device corresponds to a malicious process. In some embodiments, determining based on the hardware-based micro-architectural data whether the at least one of the one or more processes corresponds to a malicious process may include applying one or more machine-learning procedures to the hardware-based micro-architectural data to determine whether the at least one of the one or more processes corresponds to the malicious process.

Claim (Index 17):
The system of  claim 16 , wherein the one or more machine learning procedures comprise one or more of: a k-nearest neighbor procedure, a decision tree procedure, a random forest procedure, an artificial neural network procedure, a tensor density procedure, or a hidden Markov model procedure.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 94.0
- Lexical Diversity: 2.53704
- Patent Class: 726.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14778043', '14494758', '12954454', '14707977', '14086574']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2339212614004554
- 35 USC 102 Novelty (BERT): 0.5109780926567599
- Combined Prediction Score: 0.2616269445260859
- Mean Citation Score: 178.319346
- Max Citation Score: 268.35562000000004
- Similarity Product: 197.9300436622477

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

Dataset: test