The Technology for Countering the Threats of Violation in the Information Security of Cloud Infrastructure

Unlike known methods, the proposed methodology is based on the automatic calculation of exogenous parameters and does not require a universal threshold criterion. Understanding the control of malicious behavior is based on the description of attacks and the use of graph theory to combat them. When considering how to detect the malicious impact of attacks on cloud infrastructure instances. Improve the accuracy of detecting abnormal behavior: the level of short-term and medium-term false alarms is less than 7% and 5%, respectively. The positive detection rate of user attacks and abnormal behavior exceeded 75% and 80% in the short term. In the long term, it is 80%, in the medium term - 80%. The impact of automated reactive control allows you to automatically identify types of unauthorized transactions in short-term and medium-term forecasts with an accuracy of more than 80% and 78%, respectively.

Authors

Institutions

Publication Details

Published
2024-10-16
DOI
https://doi.org/10.1109/csit65290.2024.10982655
Primary Topic
Economic and Technological Systems Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Technology for Countering the Threats of Violation in the Information Security of Cloud Infrastructure

Iryna Artyshchuk, Olexander Belej, Maksym Kutelmakh
Economic and Technological Systems Analysis
article

The Technology for Countering the Threats of Violation in the Information Security of Cloud Infrastructure

Iryna Artyshchuk, Olexander Belej, Maksym Kutelmakh
article en

Abstract

Unlike known methods, the proposed methodology is based on the automatic calculation of exogenous parameters and does not require a universal threshold criterion. Understanding the control of malicious behavior is based on the description of attacks and the use of graph theory to combat them. When considering how to detect the malicious impact of attacks on cloud infrastructure instances. Improve the accuracy of detecting abnormal behavior: the level of short-term and medium-term false alarms is less than 7% and 5%, respectively. The positive detection rate of user attacks and abnormal behavior exceeded 75% and 80% in the short term. In the long term, it is 80%, in the medium term - 80%. The impact of automated reactive control allows you to automatically identify types of unauthorized transactions in short-term and medium-term forecasts with an accuracy of more than 80% and 78%, respectively.

Lviv Polytechnic National University (UA)
Industry, innovation and infrastructure
Openalex Percentile: Top 53%
Economic and Technological Systems Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.