Work

Integration of Artificial Intelligence in Intrusion Detection and Prevention Systems

Year: 2025

Type: article

Abstract: This article focuses on the integration of artificial intelligence (AI) into Intrusion Detection and Prevention Systems (IDPS) in response to the rapid evolution of security threats. Traditional signature-based security approaches are unable to cope with complex and advanced attacks. AI-based IDPS use machine learning, deep learning and natural language processing to analyze large volumes of data, detect anomalies and predict emerging threats in real time. The article offers practical recommendations for organizations implementing AI-based security solutions.

Source: Annual of Konstantin Preslavsky University of Shumen Faculty of mathematics and informatics

DOI: 10.46687/zmzc7716

Authors: STOYAN STOYANOV, TEODORA STOYANOVA, RADOSTIN RAFAILOV

Institution: Shumen University

Language: English

Topic: Network Security and Intrusion Detection

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: Constantine of Preslav University of Shumen

OpenAlex ID: W4416632909

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