ENSURING OBJECT SECURITY AND ANALYZING INFORMATION SECURITY BASED ON NEURAL NETWORKS
DOI:
https://doi.org/10.5281/zenodo.20780950Abstract
In the context of increasingly complex cyber threats, there is an urgent need for innovative approaches capable
of effectively identifying and mitigating potential risks. Neural networks offer a promising solution to these challenges
through their risk detection and prediction capabilities. This research explores various neural network architectures and
their applications in identifying and mitigating potential security breaches. Neural network-based systems significantly
improve the resilience of defense tools against cyberattacks and provide robust protection for critical information assets.
Keywords
defense object, neural networks, information security, artificial immune system, Bayesian networkReferences
Silva L., Santos A., Silva J., Montes A. A Neural Network Application for Attack Detection in Computer Networks //
Proc. of Intern. Joint Conf. on Neural Network. 2004.
Zhou Y. P. Hybrid Model Based on Artificial Immune System and PCA Neural Networks for Intrusion Detection // Asia-
Pacific Conf. on Information Processing. 2009.
Браницкий А. А., Котенко И. В. Обнаружение сетевых атак на основе комплексирования нейронных,
иммунных и нейронечетких классификаторов // Информационно-управляющие системы. 2015.
Котенко И. В., Саенко И. Б., Полубелова О. В., Чечулин А. А. Применение технологии управления
информацией и событиями безопасности для защиты информации в критически важных инфраструктурах //
Тр. СПИИРАН. 2012.
Downloads
Published
How to Cite
Issue
Section
