A lightweight cryptographic algorithm for the transmission of images from road environments in self-driving  

作　　者：Runchen Gao Shen Li Yuqi Gao Rui Guo 

机构地区：[1]School of Cyberspace Security,Xi’an University of Posts&Telecommunications,Xi’an 710121,China [2]School of Telecommunication and Information Engineering,Xi’an University of Posts&Telecommunications,Xi’an 710121,China

出　　处：《Cybersecurity》2018年第1期1-11,共11页网络空间安全科学与技术（英文）

基　　金：supported by the National Natural Science Foundation of China under Grant 61802303,61772418 and 61602378;the Key Research and Development Program of Shaanxi under Grant 2020ZDLGY08-04 and 2019KW-053;the Innovation Capability Support Program in Shaanxi Province of China under Grant 2020KJXX-052 and 2017KJXX-47;the Natural Science Basic Research Plan in Shaanxi Province of China under Grant 2019JQ-866,2018JZ6001 and 2016JM6033;the Research Program of Education Bureau of Shaanxi Province under Grant 19JK0803;the New Star Team of Xi’an University of Posts and Telecommunications under Grant 2016-02.

摘　　要：With the large-scale application of 5G in industrial production,the Internet of Things has become an important technology for various industries to achieve efficiency improvement and digital transformation with the help of the mobile edge computing.In the modern industry,the user often stores data collected by IoT devices in the cloud,but the data at the edge of the network involves a large of the sensitive information,which increases the risk of privacy leakage.In order to address these two challenges,we propose a security strategy in the edge computing.Our security strategy combines the Feistel architecture and short comparable encryption based on sliding window(SCESW).Compared to existing security strategies,our proposed security strategy guarantees its security while significantly reducing the computational overhead.And our GRC algorithm can be successfully deployed on a hardware platform.

关 键 词：5G Internet of things(IoT) Mobile edge computing Feistel architecture SCESW GRC algorithm 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]