PATENT CLAIM ANALYSIS

Application Number: 15924859
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-09
Patent Classification: ["726", "022000"]

Abstract:
Malware detection techniques that detect malware by identifying the C&C communication between the malware and the remote host, and distinguish between communication transactions that carry C&C communication and transactions of innocent traffic. The system distinguishes between malware transactions and innocent transactions using malware identification models, which it adapts using machine learning algorithms. However, the number and variety of malicious transactions that can be obtained from the protected network are often too limited for effectively training the machine learning algorithms. Therefore, the system obtains additional malicious transactions from another computer network that is known to be relatively rich in malicious activity. The system is thus able to adapt the malware identification models based on a large number of positive examples—The malicious transactions obtained from both the protected network and the infected network. As a result, the malware identification models are adapted with high speed and accuracy.

Claim (Index 17):
The non-transitory computer-readable medium of  claim 16 , wherein querying the reputation database identifies a reputation level of a host participating in the malicious transaction.

Metadata:
- Claim Count in Document: 46.0
- Percentile: 90.0
- Lexical Diversity: 1.92771
- Patent Class: 726.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['14295758', '13874339', '14060933', '13895271', '12971413']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3503644867171808
- 35 USC 102 Novelty (BERT): 0.559926776664781
- Combined Prediction Score: 0.3713207157119408
- Mean Citation Score: 238.419838
- Max Citation Score: 374.7525
- Similarity Product: 232.48660471200944

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