Threat Foresight: Web Threat Detection and Forecasting Trends and Insights
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.
Authors
- Irfan Ali Syed (ORCID: https://orcid.org/0000-0002-9539-1870)
- Krutika Dwarka Naidu
- Sujal Shyam Hasoriya
- Sujal Ganvir
Institutions
- Rashtrasant Tukadoji Maharaj Nagpur University (IN)
Publication Details
- Journal
- International Journal of Scientific Research in Science and Technology
- Published
- 2025-03-04
- DOI
- https://doi.org/10.32628/ijsrst25122209
- Primary Topic
- Spam and Phishing Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00