Cloud-Based Big Data Security Models for Financial Institutions

Abstract

Financial institutions face ever-increasing security challenges, prominently reflected in the dramatically rising number of breaches and incidents. Many of these institutions are undergoing a transformation in the way the deploy, and consume IT services. Rather than the traditional ‘Over-provision’ approach – in terms of scalability, complexity, risk, cost and time to deploy; the Cloud model enables firms to ‘under-provision’ provision only what is required and ‘elastic’. Cloud computing enables banks and financial institutions to deploy their infrastructure, platform and software in a more efficient manner. Cloud-based IT systems offer significant economic and scalability advantages but in the financial sector where sensitive, private and confidential information is actively processed such solutions also present a significantly increased risk and need to provide a more wooden security model compared to on-premise legacy solutions.
Banking and financial services institutions use cloud models for their infrastructure, platform, and Software-as-a-Service needs. These cloud-based deployment models enable banks to meet their business and operational needs efficiently and garner substantial savings. However, while many financial institutions have witnessed the benefits of cloud computing, security considerations inherent to these systems have hindered and delayed their mass adoption. Security is considered the most important barrier for adopting public clouds. Since all cloud services rely on the internet for service delivery, the Internet’s credibility is the main concern for the financial and banking sector. The sensitive nature of information processed and stored in such environments makes data security of utmost importance and financial service providers should approach data storage and management issues while keeping in mind the impact it might have on their reputation if they have to face a data loss incident.