Survey on Security Monitoring and Intrusion Detection in the Big Data Environment

Abstract

Recently, new cities have appeared called smart cities (SC) that use electronic devices to manage and transfer information. These electronic devices are interconnected via a new generation of the internet called internet of things (IoT), and are generating and transferring continuously a large mass and variety of data between them, these data transfers can contain new intrusions. However, the current information security devices cannot identify these new intrusions, and have problems with the large amount and diversity of produced data. To solve these issues, new approaches have been proposed for security monitoring and intrusion detection in a Big Data environment. In this paper, we will give an overview on these proposals and analyze them, to identify their weaknesses in order to help researchers improve information security in the future.

Exploring big data traits and data quality dimensions for big data analytics application using partial least squares structural equation modelling

“…can be linked to the inability of traditional database management tools to handle structured and unstructured data simultaneously [6]. Structured data refers to data that have a scheme, metadata, rules, and constraints to follows, whilst unstructured data have no structure at all or unknown structure to follow [7].…”