Hybrid Encryption Algorithm for Big Data Security in the Hadoop Distributed File System - Mohanraj, T.; Santhosh, R. (Computer Assisted Methods in Engineering and Science, 2022)
A large amount of structured and unstructured data is collectively termed big data. The recent technological development streamlined several companies to handle massive data and interpret future trends and requirements. The Hadoop distributed file system (HDFS) is an application introduced for efficient big data processing. However, HDFS does not have built-in data encryption methodologies, which leads to serious security threats. Encryption algorithms are introduced to enhance data security; however, conventional algorithms lag in performance while handling larger files. This research aims to secure big data using a novel hybrid encryption algorithm combining cipher-text policy attribute-based encryption (CP-ABE) and advanced encryption standard (AES) algorithms. The performance of the proposed model is compared with traditional encryption algorithms such as DES, 3DES, and Blowfish to validate superior performance in terms of throughput, encryption time, decryption time, and efficiency. Maximum efficiency of 96.5% with 7.12 min encryption time and 6.51 min decryption time of the proposed model outperforms conventional encryption algorithms.