Visible to the public Biblio

Filters: Author is Sun, Z.  [Clear All Filters]
2019-09-30
Liu, Y., Li, L., Gao, Q., Cao, J., Wang, R., Sun, Z..  2019.  Analytical Model of Torque-Prediction for a Novel Hybrid Rotor Permanent Magnet Machines. IEEE Access. 7:109528–109538.

This paper presents an analytical method for predicting the electromagnetic performance in permanent magnet (PM) machine with the spoke-type rotor (STR) and a proposed hybrid rotor structure (HRS), respectively. The key of this method is to combine magnetic field analysis model (MFAM) with the magnetic equivalent circuit model. The influence of the irregular PM shape is considered by the segmentation calculation. To obtain the boundary condition in the MFAM, respectively, two equivalent methods on the rotor side are proposed. In the STR, the average flux density of the rotor core outer-surface is calculated to solve the Laplace's equation with considering for the rotor core outer-surface eccentric. In the HRS, based on the Thevenin's theorem, the equivalent parameters of PM remanence BreB and thickness hpme are obtained as a given condition, which can be utilized to compute the air-gap flux density by conventional classic magnetic field analysis model of surface-mounted PMs with air-gap region. Finally, the proposed analytical models are verified by the finite element analysis (FEA) with comparisons of the air-gap flux density, flux linkage, back-EMF and electromagnetic torque, respectively. Furthermore, the performance that the machine with the proposed hybrid structure rotor can improve the torque density as explained.

2019-09-26
Xu, J., Ying, C., Tan, S., Sun, Z., Wang, P., Sun, Z..  2018.  An Attribute-Based Searchable Encryption Scheme Supporting Trapdoor Updating. 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech). :7-14.
In the cloud computing environment, a growing number of users share their own data files through cloud storage. However, there will be some security and privacy problems due to the reason that the cloud is not completely trusted, so it needs to be resolved by access control. Attribute-based encryption (ABE) and searchable encryption (SE) can solve fine-grained access control. At present, researchers combine the two to propose an attribute-based searchable encryption scheme and achieved remarkable results. Nevertheless, most of existing attribute-based searchable encryption schemes cannot resist online/offline keyword guessing attack. To solve the problem, we present an attribute-based (CP-ABE) searchable encryption scheme that supports trapdoor updating (CSES-TU). In this scheme, the data owner can formulate an access strategy for the encrypted data. Only the attributes of the data user are matched with the strategy can the effective trapdoor be generated and the ciphertext be searched, and that this scheme will update trapdoors at the same time. Even if the keywords are the same, new trapdoors will be generated every time when the keyword is searched, thus minimizing the damage caused by online/offline keyword guessing attack. Finally, the performance of the scheme is analyzed, and the proof of correctness and security are given at the same time.
2018-03-05
Guan, C., Mohaisen, A., Sun, Z., Su, L., Ren, K., Yang, Y..  2017.  When Smart TV Meets CRN: Privacy-Preserving Fine-Grained Spectrum Access. 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS). :1105–1115.

Dynamic spectrum sharing techniques applied in the UHF TV band have been developed to allow secondary WiFi transmission in areas with active TV users. This technique of dynamically controlling the exclusion zone enables vastly increasing secondary spectrum re-use, compared to the "TV white space" model where TV transmitters determine the exclusion zone and only "idle" channels can be re-purposed. However, in current such dynamic spectrum sharing systems, the sensitive operation parameters of both primary TV users (PUs) and secondary users (SUs) need to be shared with the spectrum database controller (SDC) for the purpose of realizing efficient spectrum allocation. Since such SDC server is not necessarily operated by a trusted third party, those current systems might cause essential threatens to the privacy requirement from both PUs and SUs. To address this privacy issue, this paper proposes a privacy-preserving spectrum sharing system between PUs and SUs, which realizes the spectrum allocation decision process using efficient multi-party computation (MPC) technique. In this design, the SDC only performs secure computation over encrypted input from PUs and SUs such that none of the PU or SU operation parameters will be revealed to SDC. The evaluation of its performance illustrates that our proposed system based on efficient MPC techniques can perform dynamic spectrum allocation process between PUs and SUs efficiently while preserving users' privacy.

2017-03-08
Sun, Z., Meng, L., Ariyaeeinia, A..  2015.  Distinguishable de-identified faces. 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG). 04:1–6.

The k-anonymity approach adopted by k-Same face de-identification methods enables these methods to serve their purpose of privacy protection. However, it also forces every k original faces to share the same de-identified face, making it impossible to track individuals in a k-Same de-identified video. To address this issue, this paper presents an approach to the creation of distinguishable de-identified faces. This new approach can serve privacy protection perfectly whilst producing de-identified faces that are as distinguishable as their original faces.