Neural Network Model for Information Security Incident Forecasting

Submitted by grigby1 on Fri, 05/08/2020 - 1:54pm

Title	Neural Network Model for Information Security Incident Forecasting
Publication Type	Conference Paper
Year of Publication	2018
Authors	Katasev, Alexey S., Emaletdinova, Lilia Yu., Kataseva, Dina V.
Conference Name	2018 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)
Date Published	May 2018
Publisher	IEEE
ISBN Number	978-1-5386-4307-5
Keywords	artificial neural network, Artificial neural networks, Biological neural networks, Collaboration, Forecasting, Information security, information security incident, information security incidents forecasting, intelligent forecasting system, Metrics, neural nets, neural network application, neural network model, Neural Network Security, neural network structure, policy-based governance, Predictive models, pubcrawl, resilience, Resiliency, security of data, time series, Time series analysis, time series prediction
Abstract	This paper describes the technology of neural network application to solve the problem of information security incidents forecasting. We describe the general problem of analyzing and predicting time series in a graphical and mathematical setting. To solve this problem, it is proposed to use a neural network model. To solve the task of forecasting a time series of information security incidents, data are generated and described on the basis of which the neural network is trained. We offer a neural network structure, train the neural network, estimate it's adequacy and forecasting ability. We show the possibility of effective use of a neural network model as a part of an intelligent forecasting system.
URL	https://ieeexplore.ieee.org/document/8728734
DOI	10.1109/ICIEAM.2018.8728734
Citation Key	katasev_neural_2018

Groups:

Science of Security VO