Intelligent API Gateway with Adaptive Rate Limiting and Malicious Detection

With the rapid proliferation of microservices architecture, API gateways have become critical components for managing, securing, and monitoring distributed systems. Traditional API gateways offer request routing and static rate limiting but lack intelligent mechanisms to detect malicious activities and adapt dynamically to evolving traffic patterns. This paper proposes an Intelligent API Gateway that integrates adaptive rate limiting, machine learning-based malicious request detection, and a real-time analytics dashboard. The system employs supervised learning models to identify attack patterns such as SQL injection, XSS, and brute-force attempts. A comprehensive logging and monitoring module provides actionable insights into API usage, request rates, and detected threats through a dynamic and interactive dashboard. Experimental results demonstrate improved detection accuracy (~92%) and system resilience compared to traditional gateways, making the proposed solution suitable for modern cloud-based and microservices applications.

Keywords: API Gateway, Adaptive Rate Limiting, Machine Learning, Cybersecurity, Microservices, Intrusion Detection, Dashboard Analytics, SQL Injection Detection

N. Shunmuga Karpagam, Srisha S, Vidhya R, Sangeetha B, Susmitha S (2026). Intelligent API Gateway with Adaptive Rate Limiting and Malicious Detection. International Journal of Innovative Research in Multidisciplinary Education & Technology (IJIRMET), 11(3).