Xidian University

About: Xidian University is a education organization based out in Xi'an, China. It is known for research contribution in the topics: Antenna (radio) & Computer science. The organization has 32099 authors who have published 38961 publications receiving 431820 citations. The organization is also known as: University of Electronic Science and Technology at Xi'an & Xīān Diànzǐ Kējì Dàxué.

The Property, Preparation and Application of Topological Insulators: A Review

Abstract: Topological insulator (TI), a promising quantum and semiconductor material, has gapless surface state and narrow bulk band gap. Firstly, the properties, classifications and compounds of TI are introduced. Secondly, the preparation and doping of TI are assessed. Some results are listed. (1) Although various preparation methods are used to improve the crystal quality of the TI, it cannot reach the industrialization. Fermi level regulation still faces challenges; (2) The carrier type and lattice of TI are affected by non-magnetic impurities. The most promising property is the superconductivity at low temperature; (3) Magnetic impurities can destroy the time-reversal symmetry of the TI surface, which opens the band gap on the TI surface resulting in some novel physical effects such as quantum anomalous Hall effect (QAHE). Thirdly, this paper summarizes various applications of TI including photodetector, magnetic device, field-effect transistor (FET), laser, and so on. Furthermore, many of their parameters are compared based on TI and some common materials. It is found that TI-based devices exhibit excellent performance, but some parameters such as signal to noise ratio (S/N) are still lower than other materials. Finally, its advantages, challenges and future prospects are discussed. Overall, this paper provides an opportunity to improve crystal quality, doping regulation and application of TI.

Efficient and Privacy-Preserving Online Medical Prediagnosis Framework Using Nonlinear SVM

Abstract: With the advances of machine learning algorithms and the pervasiveness of network terminals, the online medical prediagnosis system, which can provide the diagnosis of healthcare provider anywhere anytime, has attracted considerable interest recently. However, the flourish of online medical prediagnosis system still faces many challenges including information security and privacy preservation. In this paper, we propose an e fficient and privacy-preserving online medical pre diag nosis framework, called eDiag , by using nonlinear kernel support vector machine (SVM). With eDiag, the sensitive personal health information can be processed without privacy disclosure during online prediagnosis service. Specifically, based on an improved expression for the nonlinear SVM, an efficient and privacy-preserving classification scheme is introduced with lightweight multiparty random masking and polynomial aggregation techniques. The encrypted user query is directly operated at the service provider without decryption, and the diagnosis result can only be decrypted by user. Through extensive analysis, we show that eDiag can ensure that users’ health information and healthcare provider's prediction model are kept confidential, and has significantly less computation and communication overhead than existing schemes. In addition, performance evaluations via implementing eDiag on smartphone and computer demonstrate eDiag's effectiveness in term of real online environment.

Certificateless public auditing for data integrity in the cloud

Abstract: Due to the existence of security threats in the cloud, many mechanisms have been proposed to allow a user to audit data integrity with the public key of the data owner before utilizing cloud data. The correctness of choosing the right public key in previous mechanisms depends on the security of Public Key Infrastructure (PKI) and certificates. Although traditional PKI has been widely used in the construction of public key cryptography, it still faces many security risks, especially in the aspect of managing certificates. In this paper, we design a certificateless public auditing mechanism to eliminate the security risks introduced by PKI in previous solutions. Specifically, with our mechanism, a public verifier does not need to manage certificates to choose the right public key for the auditing. Instead, the auditing can be operated with the assistance of the data owner's identity, such as her name or email address, which can ensure the right public key is used. Meanwhile, this public verifier is still able to audit data integrity without retrieving the entire data from the cloud as previous solutions. To the best of our knowledge, it is the first certificateless public auditing mechanism for verifying data integrity in the cloud. Our theoretical analyses prove that our mechanism is correct and secure, and our experimental results show that our mechanism is able to audit the integrity of data in the cloud efficiently.

D2D Enhanced Heterogeneous Cellular Networks with Dynamic TDD

Abstract: Over the last decade, the growing amount of UL and DL mobile data traffic has been characterized by substantial asymmetry and time variations. Dynamic time-division duplex (TDD) has the capability to accommodate to the traffic asymmetry by adapting the UL/DL configuration to the current traffic demands. In this work, we study a two-tier heterogeneous cellular network (HCN) where the macro tier and small cell tier operate according to a dynamic TDD scheme on orthogonal frequency bands. To offload the network infrastructure, mobile users in proximity can engage in D2D communications, whose activity is determined by a carrier sensing multiple access (CSMA) scheme to protect the ongoing infrastructure-based and D2D transmissions. We present an analytical framework to evaluate the network performance in terms of load-aware coverage probability and network throughput. The proposed framework allows to quantify the effect on the coverage probability of the most important TDD system parameters, such as the UL/DL configuration, the base station density, and the bias factor. In addition, we evaluate how the bandwidth partition and the D2D network access scheme affect the total network throughput. Through the study of the tradeoff between coverage probability and D2D user activity, we provide guidelines for the optimal design of D2D network access.