- Patent Title: Forecasting and classifying cyber-attacks using neural embeddings
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Application No.: US15019073Application Date: 2016-02-09
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Publication No.: US09866580B2Publication Date: 2018-01-09
- 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

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 crossing over at least one the vectors of the second collection with a corresponding vector of a fourth collection, migrating at least one of the vectors of the second collection with a corresponding vector of a fifth collection, or both. 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
- US20170230398A1 FORECASTING AND CLASSIFYING CYBER-ATTACKS USING NEURAL EMBEDDINGS Public/Granted day:2017-08-10
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