Original scientific paper

https://doi.org/10.17559/TV-20230618000745

Enhanced Secure Storage of Big Data at Rest with Improved ECC and Paillier Homomorphic Encryption Algorithms

Rong Hu ; School of Intelligence Technology, Geely University of China, Chengdu Sichuan, 641423, P. R. China, No. 123, SEC. 2, Chengjian Avenue, Eastern New District, Chengdu City Sichuan Province *
Ping Huang ; School of Mathematics and Computer Science, Panzhihua University, Panzhihua, Sichuan, 617000, P. R. China No. 10, North Section of Sanxian Avenue, East District, Panzhihua City, Sichuan Province

* Corresponding author.

Abstract

With the rapid growth of Big Data, securing its storage has become crucial. This study proposes to enhance the secure storage of big data at rest in Hadoop by improving encryption algorithms. The Elliptic Curve Cryptography Algorithm (ECC) is upgraded by a parallel two-threaded approach for unstructured data. For structured data, enhance Paillier Homomorphic Encryption to support operations on ciphertexts. Experiments on datasets up to 4 G show that the modified ECC method reduces encryption time to 60 - 80 seconds, compared to 100 - 160 seconds for standard ECC, AES, and DES. It can also use shorter key lengths than RSA with comparable levels of security. Enhanced Paillier encryption uses large prime numbers to ensure the validity of the ciphertext. By combining these improved encryption techniques within a secure Hadoop framework, this research demonstrates an effective way to address vulnerabilities in Big Data storage.

Keywords

hadoop; Paillier Homomorphic Encryption; static Big Data; secure storage

Hrčak ID:

314841

URI

https://hrcak.srce.hr/314841

Publication date:

29.2.2024.

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