Secure Adaptive API Gateway with AI-Based Threat Prediction and Auto-Remediation

Durga Prasad Kouru

doi:10.70528/IJLRP.v6.i10.2102

Secure Adaptive API Gateway with AI-Based Threat Prediction and Auto-Remediation

Author(s)	Durga Prasad Kouru
Country	United States
Abstract	The Operation Programming Interfaces (APIs) serve as the central conduits for data exchange in ultramodern enterprise infrastructures, making the security of these channels a matter of critical functional significance. The proliferation of API-driven ecosystems has similarly expanded the attack surface available to vicious actors, with traditional border-grounded defences proving increasingly vulnerable against dynamic and multi-vector pitfalls. Secure adaptive API gateways, stoked with artificial intelligence (AI)-grounded trouble vaticination and bus-remediation capabilities, represent a transformative response to this growing challenge. Intelligent gateway infrastructures integrate machine literacy (ML) models to continuously cover API business, detect behavioural anomalies, and prognosticate trouble patterns before exploitation occurs. Supervised ways similar as Random Forest and Support Vector Machines identify given attack autographs, while unsupervised clustering and deep neural network models address zero-day and preliminarily unclassified attack vectors. These AI- driven mechanisms outperform stationary rule- grounded systems by conforming stoutly to evolving bushwhacker tactics, including credential filling, broken object- position authorization, shadow API exploitation, and distributed denial- of- service juggernauts. bus- remediation capabilities close the circle between discovery and response by executing pre-defined playbooks at machine speed, dramatically reducing mean time to remediate. Integrated Security Orchestration, robotization, and Response platforms enable real- time constraint conduct similar as IP blocking, rate limit enforcement, token cancellation, and endpoint isolation without taking homemade critic intervention. The practical significance of these capabilities extends to compliance readiness, as nonsupervisory fabrics decreasingly dictate nonstop monitoring and rapid-fire vulnerability resolution. Organizations that emplace adaptive, AI- enabled API gateways gain measurable advancements in security posture, functional effectiveness, and adaptability against both known and arising pitfalls.
Keywords	API Gateway Security • AI Threat Prediction • Anomaly Detection • Auto-Remediation • Machine Learning
Field	Engineering
Published In	Volume 6, Issue 10, October 2025
Published On	2025-10-10
DOI	https://doi.org/10.70528/IJLRP.v6.i10.2102
Short DOI	https://doi.org/hbwsh5

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Secure Adaptive API Gateway with AI-Based Threat Prediction and Auto-Remediation

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