Exploring Cyber Threats on Data Engineering Techniques for Identifying Security Breaches

Abstract

In the contemporary digital environment, the widespread occurrence of cyber risks requires implementing proactive strategies to protect sensitive data and maintain the integrity of organizations. The present study addresses the urgent need for effective breach detection techniques via data engineering concepts. This chapter presents a complete framework for breach detection in data engineering. The framework includes several components: data integration, pretreatment, advanced analytics, and interaction with security operations and incident response processes. A comprehensive evaluation is undertaken to determine the efficacy of the proposed framework by analyzing breach detection performance measures and incident reaction time data. The data engineering framework that has been suggested exhibits notable enhancements in the effectiveness of breach detection. These improvements are evident via the rise in true positive rates, the reduction in false positive rates, and the improvement in incident response efficiency. The framework demonstrates good trends in key measures such as accuracy, precision, recall, and mean time to detect/respond/contain/recover, indicating its usefulness in limiting the impact of security events. Organizations may increase their cyber security posture and proactively battle cyber threats by adopting creative data engineering methodologies and combining them with effective incident response procedures. The results emphasize the need to implement a systematic strategy for identifying breaches based on data-driven analysis and customized to meet the company's specific requirements.