Cluster-Based Risk Analysis For Big Data Security Framework

Nowadays, ensuring data security has become paramount as organizations leverage vast datasets for insights and decision-making. Traditional security measures struggle to address the unique challenges posed by big data's scale, velocity, and diversity. Despite the emergence of various tools and techniques, a singular solution remains elusive. This study explores the intersection of big data and security, emphasizing the need for layered security technologies and prioritized systems. It proposes a novel security model integrating advanced risk analysis and prioritization techniques, enabling organizations to tailor security measures effectively. By categorizing data based on sensitivity and criticality, this model provides a comprehensive framework for safeguarding data throughout its lifecycle. By embracing innovative methodologies, organizations can mitigate risks and protect their data assets in today's interconnected world.