Cybersecurity Strategies in Big Data Ecosystems: A Systematic Literature Review

Abstrak

The rapid growth of the big data ecosystem has significantly enhanced organizations' ability to process and analyze large-scale data while simultaneously increasing cybersecurity risks. Various cyber threats, including data breaches, malware, ransomware, and social engineering attacks, require more adaptive and comprehensive security strategies. This study aims to identify, analyze, and synthesize effective cybersecurity strategies for big data ecosystems using a Systematic Literature Review (SLR) approach. The review was conducted following the PRISMA 2020 guidelines through the stages of identification, screening, eligibility assessment, and selection of studies published between 2019 and 2025. The findings indicate that Artificial Intelligence (AI) and Machine Learning (ML) enhance real-time threat detection and anomaly identification, while blockchain technology improves authentication, data integrity, transparency, and resistance to data manipulation. Furthermore, adaptive cybersecurity governance and continuous security awareness programs play a crucial role in strengthening organizational cyber resilience. The study concludes that effective cybersecurity in big data environments requires the integration of advanced technologies, governance frameworks, and human factors. The findings provide valuable insights for researchers, practitioners, and policymakers in designing resilient and sustainable cybersecurity strategies for big data ecosystems.