An Efficient Framework for Big Data Security Based on Selection Encryption on Amazonec2

With the wide use of smart device made huge amount of information arise. This information needed new methods to deal with it from that perspective big data concept arise. Most of the concerns on big data are given to handle data without concentrating on its security. Encryption is the best use to keep data safe from malicious users. However, ordinary encryption methods are not suitable for big data. Selective encryption is an encryption method that encrypts only the important part of the message. However, we deal with uncertainty to evaluate the important part of the message. The problem arises when the important part is not encrypted. This is the motivation of the paper. In this paper we propose security framework to secure important and unimportant portion of the message to overcome the uncertainty. However, each will take a different encryption technique for better performance without losing security. The framework selects the important parts of the message to be encrypted with a strong algorithm and the weak part with a medium algorithm. The important of the word is defined according to how its origin frequently appears. This framework is applied on amazon EC2 (elastic compute cloud). A comparison between the proposed framework, the full encryption method and Toss-A-Coin method are performed according to encryption time and throughput. The results showed that the proposed method gives better performance according to encryption time, throughput than full encryption.