Detection and analysis of network security threats using artificial intelligence
Year: 2024
Type: article
Abstract: This article describes ways of detecting and analysing major security threats in network. Our research is based on a neural network created in Python language with the use of TensorFlow. With the help of artificial intelligence, we can analyse language for the presence of disinformation and propaganda. We have used BERT (Bidirectional Encoder Representations from Transformers) model, in order to catch fake, malicious and suspicious content. Basing on the BERT model, other models were created, for example HerBERT, which was trained to understand Polish. Furthermore, we have availed ourselves of DNS analysis, so we can localize IP addresses of Internet domains. In this work, we will discuss these methods of protecting information space.
Authors: Litawa, Grzegorz, Żelasko, Mateusz, Litawa, Julia
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6893226394
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