scholarly journals An Identity Privacy Protection Scheme in LTE-WLAN Heterogeneous Converged Network

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Liling Cao ◽  
Zhang Yu ◽  
Yuqing Liu ◽  
Shouqi Cao
Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1657
Author(s):  
Ke Yuan ◽  
Yingjie Yan ◽  
Tong Xiao ◽  
Wenchao Zhang ◽  
Sufang Zhou ◽  
...  

In response to the rapid growth of credit-investigation data, data redundancy among credit-investigation agencies, privacy leakages of credit-investigation data subjects, and data security risks have been reported. This study proposes a privacy-protection scheme for a credit-investigation system based on blockchain technology, which realizes the secure sharing of credit-investigation data among multiple entities such as credit-investigation users, credit-investigation agencies, and cloud service providers. This scheme is based on blockchain technology to solve the problem of islanding of credit-investigation data and is based on zero-knowledge-proof technology, which works by submitting a proof to the smart contract to achieve anonymous identity authentication, ensuring that the identity privacy of credit-investigation users is not disclosed; this scheme is also based on searchable-symmetric-encryption technology to realize the retrieval of the ciphertext of the credit-investigation data. A security analysis showed that this scheme guarantees the confidentiality, the availability, the tamper-proofability, and the ciphertext searchability of credit-investigation data, as well as the fairness and anonymity of identity authentication in the credit-investigation data query. An efficiency analysis showed that, compared with similar identity-authentication schemes, the proof key of this scheme is smaller, and the verification time is shorter. Compared with similar ciphertext-retrieval schemes, the time for this scheme to generate indexes and trapdoors and return search results is significantly shorter.


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

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

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