Biblio

Filters: Author is Kuang, Xiaoyun  [Clear All Filters]
2022-04-13
Chen, Hao, Chen, Lin, Kuang, Xiaoyun, Xu, Aidong, Yang, Yiwei.  2021.  Support Forward Secure Smart Grid Data Deduplication and Deletion Mechanism. 2021 2nd Asia Symposium on Signal Processing (ASSP). :67–76.
With the vigorous development of the Internet and the widespread popularity of smart devices, the amount of data it generates has also increased exponentially, which has also promoted the generation and development of cloud computing and big data. Given cloud computing and big data technology, cloud storage has become a good solution for people to store and manage data at this stage. However, when cloud storage manages and regulates massive amounts of data, its security issues have become increasingly prominent. Aiming at a series of security problems caused by a malicious user's illegal operation of cloud storage and the loss of all data, this paper proposes a threshold signature scheme that is signed by a private key composed of multiple users. When this method performs key operations of cloud storage, multiple people are required to sign, which effectively prevents a small number of malicious users from violating data operations. At the same time, the threshold signature method in this paper uses a double update factor algorithm. Even if the attacker obtains the key information at this stage, he can not calculate the complete key information before and after the time period, thus having the two-way security and greatly improving the security of the data in the cloud storage.
2022-07-29
Suo, Siliang, Huang, Kaitian, Kuang, Xiaoyun, Cao, Yang, Chen, Liming, Tao, Wenwei.  2021.  Communication Security Design of Distribution Automation System with Multiple Protection. 2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE). :750—754.
At present, the security protection of distribution automation system is faced with complex and diverse operating environment, and the main use of public network may bring greater security risks, there are still some deficiencies. According to the actual situation of distribution automation of China Southern Power Grid, this paper designs multiple protection technology, carries out encryption distribution terminal research, and realizes end-to-end longitudinal security protection of distribution automation system, which is effectively improving the anti-attack ability of distribution terminal.
2022-05-10
Chen, Liming, Suo, Siliang, Kuang, Xiaoyun, Cao, Yang, Tao, Wenwei.  2021.  Secure Ubiquitous Wireless Communication Solution for Power Distribution Internet of Things in Smart Grid. 2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE). :780–784.
With rapid advancement of Smart Grid as well as Internet of Things (IoT), current power distribution communication network faces the challenges of satisfying the emerging data transmission requirements of ubiquitous secure coverage for distributed power services. This paper focuses on secure ubiquitous wireless communication solution for power distribution Internet of Things (PDİoT) in Smart Grid. Detailed secure ubiquitous wireless communication networking topology is presented, and integrated encryption and communication device is developed. The proposed solution supports several State Secret cryptographic algorithm including SM1/SM2/SM3/SM4 as well as forward and reverse isolation functions, thus achieving secure wireless communication for PDİoT services.
2022-06-08
Chen, Lin, Qiu, Huijun, Kuang, Xiaoyun, Xu, Aidong, Yang, Yiwei.  2021.  Intelligent Data Security Threat Discovery Model Based on Grid Data. 2021 6th International Conference on Image, Vision and Computing (ICIVC). :458–463.
With the rapid construction and popularization of smart grid, the security of data in smart grid has become the basis for the safe and stable operation of smart grid. This paper proposes a data security threat discovery model for smart grid. Based on the prediction data analysis method, combined with migration learning technology, it analyzes different data, uses data matching process to classify the losses, and accurately predicts the analysis results, finds the security risks in the data, and prevents the illegal acquisition of data. The reinforcement learning and training process of this method distinguish the effective authentication and illegal access to data.