According to the distributed feature of cloud computing, a parallel homomorphic encryption scheme based on the MapReduce Hadoop was proposed with the combination of homomorphic encryption and MapReduce parallel framework under Hadoop environment. The concrete parallel homomorphic encrypting algorithm was implemented, and the theoretical analysis was given to prove the security and correctness of the proposed algorithm. The evaluation experiments on the cloud cluster consisting of 4 computing nodes with total 16 Central Processing Units (CPUs) show that the data encryption of the parallel homomorphic encryption algorithm can reach the speed-up radio of 13. The experimental result shows that the proposed algorithm can reduce the time cost of data encryption and can be applied to real-time applications.

In order to protect privacy of consumers in cloud computing, encrypted data storage is a feasible way. To speed up process of encryption and decryption, a parallel Advanced Encryption Standard (AES) encryption algorithm was proposed taking the characteristic of multi-nodes in cloud computing into account. The performance of the algorithm was analyzed in theory, and then experiments were conducted to demonstrate the efficiency of the designed algorithm. The experimental results show that the speed-up radio of the proposed encryption scheme can reach 15.9, and the total time cost of AES encryption can be reduced by 72.7% on the cloud cluster consisting of 4 compute nodes of total 16 CPUs.

In order to improve the operation efficiency of big module RSA (Rivest-Shamir-Adleman) signature algorithm, four prime Chinese Remainder Theorem (CRT)-RSA digital signature was suggested in this paper. The Hash function SHA512 was used to produce message digest, and CRT combining with Montgomery algorithm was applied to optimize large number modular exponentiation. The security analysis and experiment show that the new algorithm can resist some common attacks, and it has some advantages in signature efficiency.