Securing Hadoop Using Layered Approach (International Journal of Engineering and Computer Science, 2015)
Hadoop is a distributed system that provides a distributed filesystem and MapReduce batch job processing on large clusters using commodity servers. Although Hadoop is used on private clusters behind an organization’s firewalls, Hadoop is often provided as a shared multi-tenant service and is used to store sensitive data; as a result, strong authentication and authorization is necessary to protect private data.The biggest challenge for big data from a security point of view is the protection of user’s privacy. Hadoop Big Data frequently contains huge amounts of personal identifiable information and therefore privacy of users is a huge concern. Security and privacy issues are magnified by velocity, volume, and variety of big data, such as large-scale cloud infrastructures, diversity of data sources and formats, streaming nature of data acquisition, and high volume inter cloud migration. Therefore, traditional security mechanisms, which are tailored to securing small scale static (as opposed to streaming) data, are inadequate. As an increasing number of enterprises move towards production deployments of Hadoop, security continues to be an important topic. In this paper I am adding how Layered Approach: Secure Protocol complies with current and future security implementation standards providing authentication and authorization and integrating additional levels such as data encryption support.