Big Data Privacy and Security with Hybrid CP-ABE and ECC Paradigm

A potential framework for securely processing and storing large amounts of data has been Hadoop. With the help of Hadoop Distributed File System (HDFS) retention, it offers adaptable and affordable services for massive amounts of data. Unfortunately, the lack of any built-in security features in Hadoop makes it more likely that hostile attacks will be made on the data handled or stored using Hadoop. In this case, protecting the data kept in HDFS remains a difficult issue. As a result, investigators and developers have increased their focus on developing systems that would safeguard user data gathered in HDFS. Several encryption-decryption techniques have been created as a result, however as the file's size grows, so does their effectiveness. Thus, this research presented a hybrid Ciphertext Policy Attribute-Based Encryption (CP-ABE) and Elliptic Curve Cryptography (ECC) for encrypting the data. The streaming API (Plain text) data was collected from tweepy. Initially, ECC algorithm is employed for generating a secure key, which is again encrypted and decrypted using CP-ABE method. Decryption and encryption throughput, as well as decryption and encryption time, are used to assess the effectiveness of the suggested approach. Additionally, the improved effectiveness of the provided model with regard to of decryption throughput, encryption time, and decryption time has been verified by comparing with previous encryption approaches such as 3DES, ABHE, DES, CP-ABE&AES. The result indicated that the presented encryption model has attained higher throughput and less decryption and encryption time than other methods.