PATENT CLAIM ANALYSIS

Application Number: 16292352
Application Type: Utility
Filing Date: 2019-03
Publication Date: 2019-06
Patent Classification: ["726", "023000"]

Abstract:
An anti-malware system including at least one database, remote from a plurality of computers to be protected, which stores identification of computer applications resident on the computers to be protected and an application-specific communications footprint for the computer applications, and at least one server, remote from the plurality of computers to be protected, and being operative to calculate a reference computer-specific communications composite pattern based on multiple application-specific communications footprints for applications installed on the computers to be protected, calculate a current computer-specific communications composite pattern based on actual communications of at least one the plurality of computers to be protected, and provide an alert when the current computer-specific communications composite pattern of the at least one of the plurality of computers to be protected differs from the reference computer-specific communications composite pattern of the at least one of the plurality of computers to be protected.

Claim (Index 3):
A method for detecting malware according to  claim 1 , wherein at least some of said malware-characteristic data switched communication patterns are computer-type specific.

Metadata:
- Claim Count in Document: 3.0
- Percentile: 99.0
- Lexical Diversity: 3.01961
- Patent Class: 726.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14400502', '15086089', '15001272', '14055275', '10036521']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3278180329127399
- 35 USC 102 Novelty (BERT): 0.5492709568520909
- Combined Prediction Score: 0.349963325306675
- Mean Citation Score: 304.149356
- Max Citation Score: 413.73938
- Similarity Product: 355.07550651800153

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

Dataset: test