A New Wave in HDFS Data Security: Merging AES & MapReduce for Efficient Data Encryption
Yash Watarkar, Avi Jain, Dipesh Shah, Aliasgar Thanawala, Aparna Ashok Kamble · 2023
This paper proposes a robust encryption strategy for data protection within a Hadoop Distributed File System (HDFS) environment by integrating Advanced Encryption Standard (AES) and MapReduce. Leveraging the speed of the AES-128bit encryption algorithm in conjunction with the MapReduce parallel programming paradigm, the method achieves superior efficiency in the encryption of large amounts of crucial data. Furthermore, the implementation utilizes Phil Rogaway's XEX (Xor-Encrypt-Xor) XTS mode, which provides a robust defense against ciphertext manipulation and copy-and-paste attacks. This approach employs parallel mappers and reducers, known as AES-MR, to encrypt data chunks sequentially and concurrently. The paper demonstrates the efficacy and security of this method, suggesting it as a viable safety measure for safeguarding user-generated data in the HDFS context.