Global Information System for Cyber Threats with Artificial Intelligence and Convolutional Neural Networks

Message:
Article Type:
Research/Original Article (بدون رتبه معتبر)
Abstract:

Global cyberattacks significantly impact the economy, society, organizations, and individuals. Existing research on cyberattacks, particularly in providing AI-based analytical solutions to share information on cyber threats at the national level, is limited. National cybersecurity strategists require AI-based decision support systems to assess the cybersecurity posture or preparedness of a country. This paper proposes an AI-based solution that autonomously collects multidimensional data on cyber-related incidents from social media posts. The proposed system offers crucial analytical capabilities across a spectrum of cyber threats, utilizing sophisticated AI algorithms for anomaly detection, prediction, sentiment analysis, location detection, translation, and more. The system has been operational from April 21, 2021, to May 31, 2023. In 21 days, the system independently collected 30,203 records on cyber threats, covering various aspects of cyber threats. These dimensions included daily records of cyberattacks nationwide, such as ransomware, exploits, web threats, spam, malicious emails, network attacks, local contamination, and demandbased scanning. Additionally, the system obtained and analyzed 3,789 cyber-related tweets from 3,402 users in 37 different languages using AI. It also independently translated 893 non-English tweets. The proposed system is the first solution to employ Convolutional Neural Networks (CNN) for anomaly detection in the global cyber threat spectrum and for the automatic prediction of cyberattacks. The system was demonstrated to provide evidence-based decisions on global cyber threats across multiple platforms, including iOS, Android, and Windows.

Language:
Persian
Published:
Journal of New Researches in the Smart City, Volume:3 Issue: 1, 2025
Pages:
50 to 70
https://www.magiran.com/p2822506