Research on the Strengthening Path of Security Protection System of Big Data Platform

Abstract

With the rapid development of the digital economy and next-generation information technologies, big data platforms have become
critical infrastructure for government governance, industrial operations, and public services. Their security directly impacts the realization
of data resource value and the stability of societal operations. However, amid the rapid expansion of data scale and increasingly complex
platform architectures, big data platforms face diverse and systematic security risks across data collection, storage, computation, sharing, and
application. Traditional perimeter-based security models are no longer sufficient to meet current demands. In response, this paper conducts a
systematic investigation into big data platform security protection, addressing three dimensions: current state analysis, risk identification, and
implementation pathways. First, it examines the prevailing security practices of typical big data platforms and analyzes major threats using
relevant theories. Second, it identifies prominent challenges in existing security frameworks, focusing on data lifecycle management, heterogeneous component coordination, and real-time threat response. Finally, it proposes enhancement pathways for the big data platform security
framework across technical implementation, management and operations, as well as standards, regulations, and talent development. This paper aims to provide systematic and actionable recommendations for big data platform security governance, offering reference for enhancing
platform security capabilities and data element protection levels.