Invention Grant
- Patent Title: Forecasting and classifying cyber attacks using neural embeddings migration
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Application No.: US15019117Application Date: 2016-02-09
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Publication No.: US10230751B2Publication Date: 2019-03-12
- Inventor: Mohamed N. Ahmed , Aaron K. Baughman , John F. Behnken , Mauro Marzorati
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Garg Law Firm, PLLC
- Agent Rakesh Garg; Christopher K. McLane
- Main IPC: H04L29/06
- IPC: H04L29/06 ; G06N7/00 ; G06N3/08

Abstract:
A first collection including a first feature vector and a Q&A feature vector is constructed. A second collection is constructed from the first collection by inserting noise in at least one of the vectors. A third collection is constructed by migrating, at least one of a vectors of the second collection with a corresponding vector of a fourth collection. The second and the fourth collections have a property distinct from one another. Using a forecasting configuration, a vector of the third collection is aged to generate a changed feature vector, the changed feature vector containing feature values expected at a future time. The changed feature vector is input into a trained neural network to predict a probability of the cyber-attack occurring at the future time.
Public/Granted literature
- US20170230399A1 FORECASTING AND CLASSIFYING CYBER ATTACKS USING NEURAL EMBEDDINGS MIGRATION Public/Granted day:2017-08-10
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