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- 저자 : Wenbao Zhang (검색결과 3 건)
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A novel ID-based multi-domain handover protocol for mesh points in WMNs
( Xue Zhang ),( Guangsong Li ),( Wenbao Han ),( Huifang Ji ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.7
Wireless mesh networks (WMNs) provide an efficient and flexible method to the field of wireless networking, but also bring many security issues. A mesh point may lose all of its available links during its movement. Thus, the mesh point needs to handover to a new mesh point in order to obtain access to the network again. For multi-domain WMNs, we proposed a new ID-based signcryption scheme and accordingly present a novel ID-based handover protocol for mesh points. The mutual authentication and key establishment of two mesh points which belong to different trust domains can be achieved by using a single one-round message exchange during the authentication phase. The authentication server is not involved in our handover authentication protocol so that mutual authentication can be completed directly by the mesh points. Meanwhile, the data transmitted between the two mesh points can be carried by the authentication messages. Moreover, there are no restrictions on the PKG system parameters in our proposed multi-domain ID-based signcryption scheme so our handover scheme can be easily applied to real WMNs circumstances. Security of the signcryption scheme is proved in the random oracle model. It shows that our protocol satisfies the basic security requirements and is resistant to existing attacks based on the security of the signcryption. The analysis of the performance demonstrates that the protocol is efficient and suitable for the multi-domain WMNs environment.
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Baoping Guo,Zhuangzhi Zhang,Xueting Zheng,Yongzhong Guo,Li Zhao,Ren Cai,Bingjie Wang,Mei Yang,Xi Shou,Wenbao Zhang,Bin Jia 대한기생충학ㆍ열대의학회 2019 The Korean Journal of Parasitology Vol.57 No.2
Echinococcus granulosus is an important zoonotic parasite globally causing cystic echinococcosis (CE) in hu- mans and animals. In this study, prevalence of CE and variation of cox1 gene sequence were analyzed with isolates E. granulosus collected from different areas in northern Xinjiang, China. The survey showed that 3.5% of sheep and 4.1% of cattle were infected with CE. Fragment of cox1 was amplified from all the positive sheep and cattle samples by PCR. In addition, 26 positive samples across the 4 areas were included. The isolates were all E. granulosus sensu stricto (s.s.) containing 15 haplotypes (Hap1-15), and clustered into 2 genotypes, G1 (90.1%, 91/101) and G3 (9.9%, 10/101). Hap1 was the most common haplotype (48.5%, 49/101). Hap9 were found in humans samples, indicating that sheep and cattle reservoir human CE. It is indicate that E. granulosus may impact on control of CE in livestock and humans in the region.
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Huang Haolong,Cai Pingkun,Jia Wenbao,Zhang Yan 한국원자력학회 2023 Nuclear Engineering and Technology Vol.55 No.5
The grade analysis of lead-zinc ore is the basis for the optimal development and utilization of deposits. In this study, a method combining Prompt Gamma Neutron Activation Analysis (PGNAA) technology and machine learning is proposed for lead-zinc mine borehole logging, which can identify lead-zinc ores of different grades and gangue in the formation, providing real-time grade information qualitatively and semi-quantitatively. Firstly, Monte Carlo simulation is used to obtain a gamma-ray spectrum data set for training and testing machine learning classification algorithms. These spectra are broadened, normalized and separated into inelastic scattering and capture spectra, and then used to fit different classifier models. When the comprehensive grade boundary of high- and low-grade ores is set to 5%, the evaluation metrics calculated by the 5-fold cross-validation show that the SVM (Support Vector Machine), KNN (K-Nearest Neighbor), GNB (Gaussian Naive Bayes) and RF (Random Forest) models can effectively distinguish lead-zinc ore from gangue. At the same time, the GNB model has achieved the optimal accuracy of 91.45% when identifying high- and low-grade ores, and the F1 score for both types of ores is greater than 0.9.
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