Work

Cyberattack intensity forecasting on informatization objects of critical infrastructures

Year: 2019

Type: conference-paper

Abstract: 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.

Source: IOP Conference Series Materials Science and Engineering

DOI: 10.1088/1757-899x/481/1/012003

Authors: Y M Krakovsky, A N Luzgin, Y M Ivanyo

Institutions: Irkutsk State Transport University, Irkutsk State Agrarian University named after A.A. Ezhevsky

Language: English

Topic: Network Security and Intrusion Detection

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W2922051297

FWCI: 1.498

Cites: 8

Cited by: 8

Related to: 10