A Review on Security Framework and Risks across the Big Data Life Cycle

Abstract

Big data, a burgeoning concept, pertains to the management of vast volumes of data originating from diverse sources such as databases, log files, and social media posts. This data, spanning text, numbers, images, etc., manifests in structured, semi-structured, and unstructured forms. Characteristics like velocity, volume, variety, value, and complexity provide additional dimensions to the understanding of big data. As the field of big data technology evolves, it brings forth various security concerns and challenges. This paper introduces a comprehensive framework for the big data lifecycle, which encompasses four key phases: data collection, data storage, data analytics, and knowledge creation. Each phase is briefly outlined, and proceeds to delineate the associated security threats and potential attacks. By integrating the big data lifecycle with security considerations, a unified security threat model is proposed. This model serves as a foundation for conducting further research in the realm of big data security, with the ultimate goal of fortifying the infrastructure supporting big data.