System and method for the automated detection and prediction of online threats
AssigneeSeclytics, Inc.
InventorSaeed Abu-Nimeh
Life of this patent
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Abstract
A method for monitoring online security threats comprising of a machine-learning service that receives data related to a plurality of features related to internet traffic metrics, the service then processes said data by performing operations selected from among: an operation of ranking at least one feature, an operation of classifying at least one feature, an operation of predicting at least one feature, and an operation of clustering at least one feature, and as a result the machine learning service outputs metrics that aid in the detection, identification, and prediction of an attack.
Claims16
A method for alerting a client system of a potential malware threat, comprising:
- receiving a first set of network traffic data of the source system;
- extracting a first set of network traffic data features from the first set of network traffic data;
- aggregating the first set of network traffic data features to generate a trained model;
- receiving a second set of network traffic data of a target system;
- wherein the first set of network traffic data is agnostic with respect to the second set of network traffic data;
- wherein the source system is different from the target system;
- wherein the second set of network traffic data comprises a second set of network traffic data features;
- applying the trained model to the first set of network traffic data feature to score a threat level of the second set of network traffic data features;
- alerting the client system of the threat level.
Dependencies are inferred from the claim text.