A New AI-Based Semantic Cyber Intelligence Agent

The surge in cybercrime has emerged as a pressing concern contemporary society due to its far-reaching financial, social, and psychological repercussions on individuals. Beyond inflicting monetary losses, cyber-attacks exert adverse effects the social fabric well-being of affected In order mitigate deleterious consequences cyber threats, adoption an intelligent agent-based solution enhance speed comprehensiveness intelligence is advocated. this paper, novel proposed, employing four semantic agents that interact autonomously acquire crucial pertaining any given country. leverages combination techniques, including convolutional neural network (CNN), sentiment analysis, exponential smoothing, latent Dirichlet allocation (LDA), term frequency-inverse document frequency (TF-IDF), Porter stemming, others, analyse data from both media web sources. proposed method underwent evaluation 13 October 2022 6 April 2023, utilizing dataset comprising 37,386 tweets generated by 30,706 users across 54 languages. To address non-English content, total 8199 HTTP requests were made facilitate translation. Additionally, system processed 238,220 threat web. Within remarkably brief duration s, comprehensive report encompassing 7 critical dimensions for countries such Russia, Ukraine, China, Iran, India, Australia.