Machine Learning-Based Network Detection Research for SDNs by Lai Jiayue

Get full text

An efficient attribute-based encryption scheme based on SM9 encryption algorithm for dispatching and control cloud by Honghan Ji, Hongjie Zhang, Lisong Shao, Debiao He, Min Luo

Get full text

TO THE QUESTION ON THE ECONOMIC RESEARCH USING ELECTRONIC DATA BASES by Yulia A. Kreminskaya, Dmitry A. Suslov

Get full text

Research on ontology based data integration of land use by CHEN Jian-jie, YE Zhi-xuan, KE Zheng-yi

“…The research had achieved the purpose for knowledge sharing and semantic interoperation effectively, in addition, the paper gave an elementary process and main algorithms for land use data integration based on the ontology, and used a Multi-Agent method to develop a prototype.…”
Get full text

Research on image compression encoding based on fixed dictionary by Lifeng Li, Yanli Du, Yan-Hong Liu, Hua Yang

Get full text

A physically based constitutive model for 41CrS4 steel based on particle swarm optimization algorithm by Xiaoxiao Wei, Fan Tan, Peipei Yang, Hongchen Pan

Get full text

An airport apron ground service surveillance algorithm based on improved YOLO network by Yaxi Xu, Yi Liu, Ke Shi, Xin Wang, Yi Li, Jizong Chen

Get full text

UAV object tracking algorithm based on spatial saliency-aware correlation filter by Changhui Wu, Jinrong Shen, Kaiwei Chen, Yingpin Chen, Yuan Liao

Get full text

Design of digital low-carbon system for smart buildings based on PPO algorithm by Yaohuan Wu, Nan Xie

“…A smart building digital low-carbon new system based on proximal policy optimization algorithm is proposed in the research. …”
Get full text

Research on wormhole attacks in wireless mesh networks by FU Ying-fang1, ZHANG Xing1, ZHANG Ting1, LUAN Liang-yu3

Get full text

Research on ionospheric parameters prediction based on deep learning by Yuntian FENG, Xia WU, Xiong XU, Rongqing ZHANG

Get full text

Research and realization of the Trojan detection engine based on Android by Bin XIA, Feng QIU

Get full text

Research and realization of the Trojan detection engine based on Android by Bin XIA, Feng QIU

Get full text

Research on Actuator Control System Based on Improved MPC by Qingjian Zhao, Qinghai Zhang, Shuang Zhao, Xiaoqian Zhang, Shilei Lu, Yang Guo, Liqiang Song, Zhengxu Zhao

Get full text

Research on spectrum sensing technologies based on goodness of fit by Guangyue LU, Cai XU, Yinghui YE, Yin MI

“…Cognitive radio technology has achieved the dynamic allocation of spectrum resources,and improves the utilization rate of spectrum resources.Accurate and efficient spectrum sensing is the key step in cognitive radio.Developing a fast and high-performance spectrum sensing method has become an urgent problem to be solved.In recent years,goodness of fit（GOF）theory has been applied widely in the field of spectrum sensing and the effective spectrum sensing technology under small sample point has been implemented.Therefore,the research on spectrum sensing technology based on GOF has very significant value.The development process of GOF in areas of cognitive radio spectrum sensing was summarized,its basic principle common fitting criterion and fitting object were introduced.The simulation comparison of the algorithm was carried under the Gaussian channel and its prospects of further research was forecasted finally.…”
Get full text

Research on the invulnerability of regional network based on topology analysis by Changqing AN, Yujia LIU, Hui WANG, Zhiyan ZHENG, Tao YU, Jilong WANG

Get full text

Research on the invulnerability of regional network based on topology analysis by Changqing AN, Yujia LIU, Hui WANG, Zhiyan ZHENG, Tao YU, Jilong WANG

Get full text

Research on test strategy for randomness based on deep learning by Dongyu CHEN, Hua CHEN, Limin FAN, Yifang FU, Jian WANG

“…In order to achieve better test performance, researches on the randomness test strategies based on deep learning were conducted, including the batch average strategy proposed by EUROCRYPT 2021 and the selection strategy for data unit size.By introducing the randomness statistical test model based on deep learning methods, the statistical distribution and test power expression of two test strategies were theoretically derived, and it was pointed out that: (i) the batch average strategy could amplify the prediction accuracy of the model, but it was prone to an increase in the probability of the second type of error in statistics, instead reducing the statistical test power; (ii) the smaller data units of the deep model generally obtained the more powerful statistical tests.Based on the above understanding, a new bit-level deep learning model was proposed for randomness statistical tests, which gained the advantage of prediction with 80 times fewer parameters and 50% samples, compared with the previous work on linear congruent generator (LCG) algorithm, and achieved significant prediction advantages with 10～20 times fewer parameters by extending the model to apply to 5～7 rounds of Speck, compared with the model proposed by Gohr.…”
Get full text

Research on test strategy for randomness based on deep learning by Dongyu CHEN, Hua CHEN, Limin FAN, Yifang FU, Jian WANG

“…In order to achieve better test performance, researches on the randomness test strategies based on deep learning were conducted, including the batch average strategy proposed by EUROCRYPT 2021 and the selection strategy for data unit size.By introducing the randomness statistical test model based on deep learning methods, the statistical distribution and test power expression of two test strategies were theoretically derived, and it was pointed out that: (i) the batch average strategy could amplify the prediction accuracy of the model, but it was prone to an increase in the probability of the second type of error in statistics, instead reducing the statistical test power; (ii) the smaller data units of the deep model generally obtained the more powerful statistical tests.Based on the above understanding, a new bit-level deep learning model was proposed for randomness statistical tests, which gained the advantage of prediction with 80 times fewer parameters and 50% samples, compared with the previous work on linear congruent generator (LCG) algorithm, and achieved significant prediction advantages with 10～20 times fewer parameters by extending the model to apply to 5～7 rounds of Speck, compared with the model proposed by Gohr.…”
Get full text

Research on image generation technology based on deep learning by Li Jinchen

“…However, current image generation technologies still face problems such as diversity and insufficient authenticity. Based on the above problems, this paper analyzes the methods of improving and optimizing the mainstream image generation algorithm from the perspectives of improving and optimizing the loss function, improving the space modeling, revising the structure of both the generator and discriminator, while speeding up the training process. …”
Get full text