identity authentication
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Entropy ◽  
2022 ◽  
Vol 24 (1) ◽  
pp. 111
Dianjun Lu ◽  
Zhihui Li ◽  
Jing Yu ◽  
Zhaowei Han

In this paper, we present a verifiable arbitrated quantum signature scheme based on controlled quantum teleportation. The five-qubit entangled state functions as a quantum channel. The proposed scheme uses mutually unbiased bases particles as decoy particles and performs unitary operations on these decoy particles, applying the functional values of symmetric bivariate polynomial. As such, eavesdropping detection and identity authentication can both be executed. The security analysis shows that our scheme can neither be disavowed by the signatory nor denied by the verifier, and it cannot be forged by any malicious attacker.

2022 ◽  
Vol 40 (3) ◽  
pp. 1217-1231
Mingming Zhang ◽  
Jiaming Mao ◽  
Yuanyuan Ma ◽  
Liangjie Xu ◽  
Chuanjun Wang ◽  

2021 ◽  
Qikun Zhang ◽  
Liang Zhu ◽  
Yimeng Wu ◽  
Jianyong Li ◽  
Yinghui Meng ◽  

Abstract Access control technology is one of the key technologies to ensure safe resource sharing. Identity authentication and authority distribution are two key technologies for access control technology to restrict unauthorized users from accessing resources and resources can only be accessed by authorized legal users.However, user privacy protection and frequent permission changes are two thorny issues that need to be solved urgently by access control technology. To deal with these problems, this paper proposes a dynamic access control technology based on privacy protection. Compared with existing access control technologies, the main advantages of this paper are as follows: 1) encrypt and hide the attributes of entities, and use attribute-based identity authentication technology for identity authentication, which not only achieves the purpose of traditional identity authentication, but also ensures the attributes and privacy of entities are not leaked; 2) Binding resource access permissions with entity attributes, dynamically assigning and adjusting resource access control permissions through changes in entity attributes, making resource access control more fine-grained and more flexible. Security proof and performance analysis show that the proposed protocol safe under the hardness assumption of the discrete logarithm problem (DLP) and the decision bilinear Diffie-Hellman (DBDH) problem. Compared with the cited references, it has the advantages of low computational complexity, short computational time, and low communication overhead.

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Xuechun Mao ◽  
Lin You ◽  
Chengtang Cao ◽  
Gengran Hu ◽  
Liqin Hu

Biometric encryption, especially based on fingerprint, plays an important role in privacy protection and identity authentication. In this paper, we construct a privacy-preserving linkable ring signature scheme. In our scheme, we utilize a fuzzy symmetric encryption scheme called symmetric keyring encryption (SKE) to hide the secret key and use non-interactive zero-knowledge (NIZK) protocol to ensure that we do not leak any information about the message. Unlike the blind signature, we use NIZK protocol to cancel the interaction between the signer (the prover) and the verifier. The security proof shows that our scheme is secure under the random oracle model. Finally, we implement it on a personal computer and analyze the performance of the constructed scheme in practical terms. Based on the constructed scheme and demo, we give an anonymous cryptocurrency transaction model as well as mobile demonstration.

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1657
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.

Jie Zhang ◽  
Zhongmin Wang ◽  
QingLi Yan

AbstractIntelligent identity authentication in vehicle security systems, as a vital component in anti-theft system and safety driving assist system, has received wide attention. Current vehicle security systems, however, focus the car security on the car keys security, ignore the owner of car keys. Anyone who owns the car keys can operate the car. This paper introduces an intelligent identity authentication method for vehicle security system based on wireless signals. Unlike past work, our approach combines car security with car owners and car keys. The intuition underlying our design is that when a user walks towards the car, the user’s gait information can be leveraged to identify the user. We capture the user’s gait information using wireless devices which can be deployed in the car, and then extract features from the received wireless signals using convolution kernel and apply artificial neural network to identify the user. We built a prototype and experimental results show that our approach can achieve high accuracy and strong robustness.

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