EPMDA:an efficient privacy-preserving multi-dimensional data aggregation scheme for edge computing-based IoT system  

作　　者：Tao Yunting Kong Fanyu Yu Jia 

机构地区：[1]School of Software,Shandong University,Jinan 250101,China [2]College of Computer Science and Technology,Qingdao University,Qingdao 266071,China

出　　处：《The Journal of China Universities of Posts and Telecommunications》2021年第6期26-35,共10页中国邮电高校学报（英文版）

基　　金：supported by the Key Research and Development Program of Shandong Province (the Major Scientific and Technological Innovation Project of Shandong Province)(2020CXGC010114)。

摘　　要：In order to perform multi-dimensional data aggregation operations efficiently in edge computing-based Internet of things(IoT) systems, a new efficient privacy-preserving multi-dimensional data aggregation(EPMDA) scheme is proposed in this paper. EPMDA scheme is characterized by employing the homomorphic Paillier encryption and SM9 signature algorithm. To improve the computation efficiency of the Paillier encryption operation, EPMDA scheme generates a pre-computed modular exponentiation table of each dimensional data, and the Paillier encryption operation can be implemented by using only several modular multiplications. For the multi-dimensional data, the scheme concatenates zeros between two adjacent dimensional data to avoid data overflow in the sum operation of ciphertexts. To enhance security, EPMDA scheme sets random number at the high address of the exponent. Moreover, the scheme utilizes SM9 signature scheme to guarantee device authentication and data integrity. The performance evaluation and comparison show that EPMDA scheme is more efficient than the existing multi-dimensional data aggregation schemes.

关 键 词：multi-dimensional data aggregation Paillier cryptosystem Internet of things(IoT) edge computing-based 

分 类 号：TP391.44[自动化与计算机技术—计算机应用技术] TN915.08[自动化与计算机技术—计算机科学与技术]