PATENT CLAIM ANALYSIS

Application Number: 16220499
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-05
Patent Classification: ["726", "023000"]

Abstract:
According to some embodiments, a method for training a malware detector comprising a deep learning algorithm is described, which comprises converting a set of malware files and non malware files into vectors by using a feature based dictionary, and/or by using a conversion into an image, and providing prospects that the files constitute malware. Various features and combinations of features are described to build a feature based dictionary and adapt its size. According to some embodiments, a method for detecting a malware by using a malware detector comprising a deep learning algorithm is described, which comprises converting a file into a vector by using a feature based dictionary, and/or by using a conversion into an image, and providing prospects that the file constitutes malware. Methods for providing a plurality of prospects and aggregating these prospects are provided. Additional methods and systems in the field of malware detection are also described.

Claim (Index 20):
A non-transitory storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform a method of building a dictionary, for adapting files to the input of a malware detector comprising a deep learning algorithm, comprising:\n building a first size dictionary, said building comprising extracting features from a plurality of malware files and non-malware files, building a second size dictionary of lower size than the first size dictionary, wherein said building comprises selecting a subset of the features of the first size dictionary and forming the second size dictionary based at least on said subset of features, wherein the second size dictionary dictates, for files to be fed to the malware detector, the size and the content of vectors representing said files and suitable for being processed by the deep learning algorithm, for determining the prospects of whether said files constitute malware or not.

Metadata:
- Claim Count in Document: 4.0
- Percentile: 98.0
- Lexical Diversity: 2.4697
- Patent Class: 726.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14929902', '13163010', '14038682', '14985944', '15639805']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2609599533126762
- 35 USC 102 Novelty (BERT): 0.6079841561740591
- Combined Prediction Score: 0.2956623735988145
- Mean Citation Score: 261.399308
- Max Citation Score: 537.14636
- Similarity Product: 514.5200372492169

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

Dataset: test