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Threat Foresight: Web Threat Detection and Forecasting Trends and Insights

Author

Listed:
  • Krutika Dwarka Naidu
  • Syed Irfan Ali
  • Sujal Shyam Hasoriya
  • Sujal Ganvir

Abstract

The increasing sophistication and frequency of web threats necessitate advanced analytics and forecasting techniques to mitigate potential cyber risks. Traditional security measures, while effective to some extent, often struggle to adapt to evolving cyber threats. The advent of Artificial Intelligence (AI) and Generative AI (GenAI) has introduced novel methodologies for detecting, analyzing, and predicting web-based threats. This review paper explores the landscape of web threat analytics, evaluates traditional and modern forecasting techniques, and examines the role of AI and GenAI in enhancing cybersecurity. Furthermore, it highlights the challenges, limitations, and future directions in web threat analytics to guide future research and development.

Suggested Citation

  • Krutika Dwarka Naidu & Syed Irfan Ali & Sujal Shyam Hasoriya & Sujal Ganvir, 2025. "Threat Foresight: Web Threat Detection and Forecasting Trends and Insights," International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 12(2), pages 129-133, April.
    • Handle: RePEc:etm:ijsrst:v12:y2025:i2:id:638
    DOI: 10.32628/IJSRST25122209
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