Cyberattack intensity forecasting on informatization objects of critical infrastructures

4th International Conference on Safety Problems of Civil Engineering Critical Infrastructures

土木建筑工程

Krakovsky, Y.M.^1 ; Luzgin, A.N.^2 ; Ivanyo, Y.M.^3

Irkutsk State Transport University, 15 Chernyshevskogo Street, Irkutsk

664074, Russia^1

Administration of Irkutsk City, 14 Lenina, Irkutsk

664025, Russia^2

Irkutsk State Agrarian University Named after A.A. Ezhevsky, Irkutsk

664038, Russia^3

关键词: Cluster models;    Dynamic updating;    Informatization;    Interval forecasting;    Probabilistic neural networks;    Regulatory documents;    Scientific researches;    Smoothing parameter;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/481/1/012003/pdf
DOI  :  10.1088/1757-899X/481/1/012003

学科分类：土木及结构工程学

来源: IOP

【 摘 要 】

In regulatory documents of recent years in the field of information security, much attention is paid to information systems of critical infrastructures. This, in turn, justifies the need for scientific research on the development of new methods of protection against cyberattacks on such information systems. For this task, interval forecasting is recommended based on a probabilistic neural network with dynamic updating of the smoothing parameter. As benchmarks for comparing the interval forecasting results, the naive Bayesian model and the probabilistic cluster model were chosen.