Threat Detection Using Real-Time Data Engineering Pipelines

Abstract

Due to rising cyber threats and data quantities, existing systems need better threat detection. Real-time data engineering pipelines boost threat detection in this research. This study uses 2016–2020 literature data to examine threat detection methodologies, tools, and models. Results suggest that data security, integration, and standardisation must be addressed before broad use of these pipelines, despite their obvious advantages. Machine learning, blockchain, and IoT are promising.