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Research Paper | Computer Science and Information Technology | Volume 14 Issue 3, March 2025 | Pages: 341 - 345 | United States
Enhancing Java API Security with AI and Machine Learning: Smarter Defenses for a Safer Digital World
Abstract: Securing Java APIs is vital in today's interconnected world. APIs are gateways for data exchange. They face constant threats, such as unauthorized access and malicious payloads. With the rise of artificial intelligence (AI) and machine learning (ML), traditional security measures like HTTPS, OAuth 2.0, and JSON Web Tokens (JWT) can now integrate advanced threat detection. AI and ML offer real - time anomaly detection, token validation, and communication layer protection. They help identify threats earlier, reducing the risks of data breaches. This article looks at the role of AI and ML in enhancing Java API security. It discusses their use in detecting threats, ensuring token integrity, and maintaining secure communication. These technologies strengthen API defense mechanisms, enabling safer and more reliable digital ecosystems.
Keywords: Java APIs, artificial intelligence, machine learning, API security, threat detection, HTTPS, OAuth 2.0, JWT, anomaly detection
How to Cite?: Srinivas Adilapuram, "Enhancing Java API Security with AI and Machine Learning: Smarter Defenses for a Safer Digital World", Volume 14 Issue 3, March 2025, International Journal of Science and Research (IJSR), Pages: 341-345, https://www.ijsr.net/getabstract.php?paperid=SR25307091014, DOI: https://dx.doi.org/10.21275/SR25307091014