SecureMR: A Service Integrity Assurance Framework for Map Reduce

MapReduce has become increasingly popular as a powerful parallel data processing model. To deploy Map Reduce as a data processing service over open systems such as service oriented architecture, cloud computing, and volunteer computing, we must provide necessary security mechanisms to protect the integrity of Map Reduce data processing services. In this paper, we present SecureMR, a practical service integrity assurance framework for Map Reduce. SecureMR consists of five security components, which provide a set of practical security mechanisms that not only ensure Map Reduce service integrity as well as to prevent replay and Denial of Service (DoS) attacks, but also preserve the simplicity, applicability and scalability of Map Reduce. We have implemented a prototype of SecureMR based on Hadoop, an open source Map Reduce implementation. Our analytical study and experimental results show that SecureMR can ensure data processing service integrity while imposing low performance overhead.