Information Systems Risk in Big Data

2019-04-22

Rapid advances in technologies for collecting data lead to the transformation of many historically data-poor disciplines, e.g., biological sciences, health sciences, social sciences, into increasingly data-rich disciplines. This has led to exponential increases in the volume, velocity, and variety of data, i.e., “big data”. The emerging focus on Big Data is concerned with the exploration, development, and applications of scalable algorithms, infrastructures, and tools for organizing, integrating, retrieving, analyzing, and visualizing large, complex and heterogeneous data.

With the fast development of Big Data solutions and complex information systems, a variety of paradigms and platforms are emerging as value creators or improvers in multiple industries. However, the concern of information systems risk, including information security, personal data disclosure, emergent decision and disaster recovery have also arisen, which impacts on both firms and users. It is important for researchers in different areas to be aware of the information systems risk in Big Data.

The aim of this session is to provide a forum to disseminate and discuss information systems risk in big data, with special attention to security risk of complex and intelligent information systems. We want to offer an opportunity for researchers and practitioners to identify new promising research directions in this area.

Scope and Topics:

Risk assessment

Emergent management

Network security

Information privacy

Disaster recovery

Data mining

Data analysis and visualization

Model and optimization

Risk management rules

Policy and regulation

Applications