Blockchain-based privacy protection scheme for smart park multi-energy fusion system

Author(s):  
Guanlin Si ◽  
Yue Zhang ◽  
Yue Sun ◽  
Wei Chen
Author(s):  
Mingyue Zhang ◽  
Junlong Zhou ◽  
Gongxuan Zhang ◽  
Longxia Huang ◽  
Tian Wang ◽  
...  

2021 ◽  
Vol 560 ◽  
pp. 183-201
Author(s):  
Lei Zhang ◽  
Desheng Liu ◽  
Meina Chen ◽  
Hongyan Li ◽  
Chao Wang ◽  
...  

Author(s):  
Niu Yukun ◽  
Tan Xiaobin ◽  
Chen Shi ◽  
Wang Haifeng ◽  
Yu Kai ◽  
...  

2020 ◽  
Vol 1601 ◽  
pp. 032019
Author(s):  
Bangyan Kou ◽  
Suzhen Cao ◽  
Jia Lv

2018 ◽  
Vol 14 (11) ◽  
pp. 40
Author(s):  
Bohua Guo ◽  
Yanwu Zhang

<p class="0abstract"><span lang="EN-US">To improve the data aggregation privacy protection scheme in wireless sensor network (WSN), a new scheme is put forward based on the privacy protection of polynomial regression and the privacy protection method based on the homomorphic encryption. The polynomial data aggregation (PRDA+) protocol is also proposed. In this scheme, the node and the base station will pre-deploy a secret key, and the random number generator encrypts the random number for the seed through the private key, which protects the privacy of the data. Then, by comparing the decrypted aggregate data through the correlation between the two metadata, the integrity protection of the data is realized. A weighted average aggregation scheme that can be verified is proposed. In view of the different importance of user information, the corresponding weights are set for each sensor node. EL Gamal digital signature is used to authenticate sensor nodes. The results show that the signature verification algorithm enables the scheme to resist data tampering and data denial, and to trace the source of erroneous data.</span></p>


2019 ◽  
Vol 28 (09) ◽  
pp. 1950147
Author(s):  
Lei Zhang ◽  
Jing Li ◽  
Songtao Yang ◽  
Yi Liu ◽  
Xu Zhang ◽  
...  

The query probability of a location which the user utilizes to request location-based service (LBS) can be used as background knowledge to infer the real location, and then the adversary may invade the privacy of this user. In order to cope with this type of attack, several algorithms had provided query probability anonymity for location privacy protection. However, these algorithms are all efficient just for snapshot query, and simply applying them in the continuous query may bring hazards. Especially that, continuous anonymous locations which provide query probability anonymity in continuous anonymity are incapable of being linked into anonymous trajectories, and then the adversary can identify the real trajectory as well as the real location of each query. In this paper, the query probability anonymity and anonymous locations linkable are considered simultaneously, then based on the Markov prediction, we provide an anonymous location prediction scheme. This scheme can cope with the shortage of the existing algorithms of query probability anonymity in continuous anonymity locations difficult to be linked, and provide query probability anonymity service for the whole process of continuous query, so this scheme can be used to resist the attack of both of statistical attack as well as the infer attack of the linkable. At last, in order to demonstrate the capability of privacy protection in continuous query and the efficiency of algorithm execution, this paper utilizes the security analysis and experimental evaluation to further confirm the performance, and then the process of mathematical proof as well as experimental results are shown.


2018 ◽  
Vol 9 (4) ◽  
pp. 3313-3320 ◽  
Author(s):  
Jia Zhao ◽  
Jiqiang Liu ◽  
Zhan Qin ◽  
Kui Ren

2019 ◽  
Vol 148 ◽  
pp. 142-150 ◽  
Author(s):  
Hao Wang ◽  
Guangjie Han ◽  
Lina Zhou ◽  
James Adu Ansere ◽  
Wenbo Zhang

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 78551-78558 ◽  
Author(s):  
Guibing Guo ◽  
Tianzhi Yang ◽  
Yuan Liu

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