Cybersecurity In Devops: Integrating Data Privacy And Ai-Powered Threat Detection For Continuous Delivery

Abstract

As cyber threats scale, pace, and sophistication, CI/CD processes needed for DevOps require substantial and adequate security measures capable of maintaining security at the same velocity. Legacy security models may not work well for complex and fast-paced DevOps environments that require constant monitoring and protection from emerging threats. This can be avoided by employing AI as a threat detection solution, as AI can learn from past data, see patterns, identify potential threats, and respond to them in real-time. This paper draws on research and investigates the use of AI solutions in continuous delivery environments and how such solutions confront data privacy and security issues. It is more concerned with using AI and machine learning power to construct intelligent and self-driven mechanisms for threat identification and prevention before it incurs damage to DevOps. Such advancements can help minimize the chances of data leaks, which is essential in fulfilling data privacy laws and maintaining software delivery's security and completeness.

Published Date: 4 February 2021