2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)最新文献

A Multimodal Deep Network Model for Android Malware Detection Using Permission 基于权限的Android恶意软件检测的多模态深度网络模型

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563414

Wei Gu

{"title":"A Multimodal Deep Network Model for Android Malware Detection Using Permission","authors":"Wei Gu","doi":"10.1109/ICETCI53161.2021.9563414","DOIUrl":"https://doi.org/10.1109/ICETCI53161.2021.9563414","url":null,"abstract":"The Android platform has grown rapidly over the recent years. Nevertheless, the variant malicious attacks are also increasing due to its popularity and flexibility. Common malicious behaviors, such as privacy and sensitive information theft, pose a serious threat to the economic security and privacy security of users. Android uses a permission-related access control mechanism to limit the operations that a process can perform. In this paper, we propose a multimodal malware detection model MDNMDroid to mine the potential relationship between permissions by combining two different networks. Compared with single network, multimodal network can have more powerful learning ability and filter out more meaningful features for distinguishing malicious and benign samples. Evaluation results based on collected permission dataset demonstrate that MDNMDroid achieves 93.18% accuracy. Besides, we compare our malware detection model with the state-of-the-art related approaches, containing the popular deep learning models and the classical machine learning models. The comparative experimental results further show that MDNMDroid is an effective method in malware detection task.","PeriodicalId":170858,"journal":{"name":"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115444185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Improving the Quality of Service for B2B Customers with Digital Business Solutions 通过数字业务解决方案提高B2B客户的服务质量

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563509

Maryana Ivanova, O. Efimova, Boris V. Igolnikov, Georgii Gonsales Luchinin

引用次数: 0

The Boundary Problem of Stator Insulation Calculation of Large Hydrogenerator and Three-dimensional Finite Element Analysis and Exploration of Electric Field 大型水轮发电机定子绝缘计算边界问题及电场三维有限元分析与探讨

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563608

Dongyi Li, G. Xiao, Z. Dai, He Wang

引用次数: 0

An Adaptive Image Encryption Scheme Using Fractal Dynamical System and DNA Operations 基于分形动力系统和DNA操作的自适应图像加密方案

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563513

Ruisong Ye, Huiqing Huang

引用次数: 0

Fault Diagnosis Method of Gearbox Based on Dual-Tree Complex Wavelet Packet Transform and IBA-BP 基于双树复小波包变换和IBA-BP的齿轮箱故障诊断方法

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563558

Pengyu Wang, Yunfei Ding

引用次数: 0

Prediction of visceral fat area of bioelectrical impedance based on ensemble learning 基于集成学习的内脏脂肪区生物电阻抗预测

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563573

Lun Li, Wu Huang, Tao Zhang

{"title":"Prediction of visceral fat area of bioelectrical impedance based on ensemble learning","authors":"Lun Li, Wu Huang, Tao Zhang","doi":"10.1109/ICETCI53161.2021.9563573","DOIUrl":"https://doi.org/10.1109/ICETCI53161.2021.9563573","url":null,"abstract":"Visceral fat as an important indicator of body composition largely reflects the health level of the human body. However, accurate measurement of visceral fat is still a big challenge. In this work, a new ensemble learning method named ByStepStack is proposed for visceral fat area prediction. The method is divided into two steps. In the first step, the mapping relationship model from the bioelectrical impedance to the body composition is obtained by Ridge regression. The second step is to predict the visceral fat area based on the body composition obtained from the previous step. The main innovation of the proposed method is using body composition to supervise feature representation, which can be a bridge between bioelectrical impedance and the visceral fat area. Finally, our method as well as the other state of the art ensemble learning methods is applied to predict visceral fat area on the same data set. The experimental results show that the proposed ByStepStack outperforms the other existing methods. Its relative error, average absolute error, mean square error and the determinable coefficients reach 0.0352, 2.237, 10. 7033, 0.9864 respectively.","PeriodicalId":170858,"journal":{"name":"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114203012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A supervisory and governance mechanism for power master-slave chain architecture 一种权力主从链架构的监督治理机制

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563419

Xiaoyi Wang, Weiwei Qiu, Lei Zeng, Hongkai Wang, Yiyang Yao, Dong He

引用次数: 0

Discussion on the Standard and Evaluation of Communication Equipment Testing 通信设备测试标准与评估的探讨

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563416

X. Jiren, Liu Tongzan, Pei Kunpong, Wu Dongsheng, Z. Xiaolan

引用次数: 0

The co-evolution propagation model of information and epidemic based on information maximizing influence 基于信息影响最大化的信息与疫情协同进化传播模型

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563470

Yaqiong Wang, Liu Zhiqian, Guanghui Yuan

{"title":"The co-evolution propagation model of information and epidemic based on information maximizing influence","authors":"Yaqiong Wang, Liu Zhiqian, Guanghui Yuan","doi":"10.1109/ICETCI53161.2021.9563470","DOIUrl":"https://doi.org/10.1109/ICETCI53161.2021.9563470","url":null,"abstract":"In this paper, from the perspective of improving the effect of scientific early warning information, the co-evolution propagation model of information and epidemic is studied. In order to improve the quality of information in the network, the co-evolution propagation model of information and epidemic is controlled based on the research on the co-evolution propagation model of information and epidemic from the perspective of improving the effect of positive information. It improves the quality of information in the network information layer by using the influential individuals in the social network. This paper will build a co-evolution propagation model of information and epidemic based on the maximization of influence. It combines the calculation method of individual influence in order to use the influential individuals in social networks to improve the transmission efficiency of epidemic warning information. And it tries to improve the quality of information and the effect of early warning with less control and less cost. Through theoretical analysis and numerical simulation analysis, it is found that the influence of information on individual behavior plays a greater role in the co-evolution propagation model of information and epidemic. At the same time, by increasing the information transmission rate and influential individuals in the network information layer, the number of infectious epidemic will be reduced. To a certain extent, it shows that information early warning plus influence control is effective.","PeriodicalId":170858,"journal":{"name":"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125695131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LTE-M System Design and Performance Test of FAO Urban Rails 粮农组织城市轨道LTE-M系统设计与性能测试

2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) Pub Date : 2021-08-27 DOI: 10.1109/ICETCI53161.2021.9563483

Yuyuan Pu, Hongli Zhao

引用次数: 1