Authors:
Avinash Reddy Pothu

Addresses:
Department of Research and Development, Ginger Labs, Texas, United States of America.

Abstract:

Application security has become a top priority in SDLCs and CI/CD pipelines as cyber threats grow increasingly sophisticated. Meet Garlic Gate, a state-of-the-art, machine learning-powered framework that integrates effortlessly with SDLC and CI/CD processes to protect your applications. Its advanced architecture is designed to adapt to changing vulnerabilities, offering real-time threat detection, risk assessment, and dynamic learning to prevent or mitigate security issues. Using AI-driven algorithms, Garlic Gate overcomes the challenges of traditional application security methods, such as inefficient static code analysis, slow remediation timelines, and weak integration with modern CI/CD pipelines. The results are significant: reduced vulnerabilities, faster deployment cycles, and stronger defenses against new threats. This innovation represents a major leap forward in incorporating AI into every stage of application development, reshaping security practices, and advancing the discussion around secure software engineering. Garlic Gate demonstrates a groundbreaking approach, proving that software systems can be both highly efficient and more resilient than ever before.

Keywords: Application Security; Artificial Intelligence (AI); Software Development Life Cycle (SDLC); Continuous Integration/Continuous Delivery (CI/CD); Cybersecurity Methodologies.

Received on: 26/02/2024, Revised on: 05/05/2024, Accepted on: 11/07/2024, Published on: 09/09/2024

DOI: 10.69888/FTSCS.2024.000259

FMDB Transactions on Sustainable Computing Systems, 2024 Vol. 2 No. 3, Pages: 119-130

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