A Novel Approach of Ontology-Based Cyber Attack Detection and Prevention System Using AI

As the number of devices communicating information over the Internet increases daily, the need for protection is becoming a significant threat to civilization. Today's information-based society makes an ever-increasing and significant focus on digital security. There are a substantially wider range of threats and attack patterns due to the introduction of digital transformation in our lives. The advancement of technology creates security issues due to experts in cyber security's knowledge of the most recent developments. Experts need a t of help to prevent cyber-attacks and security breaches because the connection between organizations leads to “breaches in security”, and “increase in security attack vectors”, “heavy traffic” all of which are difficult tasks for humans to control. The availability of an automated and efficient method for detecting cyber threats is one of the most significant challenges in cyber security. Due to the threats that are developing in this post-COVID world, a number of forms of Artificial Intelligence (AI) are used at the forefront of triggering innovations in digital security. This analysis describes a novelapproach of ontology-based cyber-attack detection and prevention using AI. Multiclass Convolutional Neural Network (CNN) is used to detect the threats. This approach will detects and prevents the cyber attacks and protect the system.