Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China最新文献_第2页

Cross-social-network Interconnection Model Based on Bridge Community 基于桥梁社区的跨社会网络互联模型

Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China Pub Date : 1900-01-01 DOI: 10.4108/eai.29-6-2019.2282012

Min Hu, Mengyuan Dong

引用次数: 0

Supervised Machine Learning based Routing Detection for Smart Meter Network 基于监督机器学习的智能电表网络路由检测

Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China Pub Date : 1900-01-01 DOI: 10.4108/eai.29-6-2019.2283068

Raqibul Hasan, Yanxiao Zhao, Guodong Wang, Yu Luo, Lina Pu, Rui Wang

{"title":"Supervised Machine Learning based Routing Detection for Smart Meter Network","authors":"Raqibul Hasan, Yanxiao Zhao, Guodong Wang, Yu Luo, Lina Pu, Rui Wang","doi":"10.4108/eai.29-6-2019.2283068","DOIUrl":"https://doi.org/10.4108/eai.29-6-2019.2283068","url":null,"abstract":"It is known that the Ad hoc On-Demand Distance Vector (AODV) routing protocol for smart meter network is vulnerable to denial of service attacks (e.g., black hole attack and selective forwarding attack). In this paper, we introduce supervised machine learning to detect unknown routing attacks under AODV. There are two problems in the existing intrusion detection algorithms. The first problem is that the existing intrusion detection algorithms are mainly applied to a specific and known type of routing attack, which no longer work for unknown attacks. The second one is that constant thresholds are commonly used for detection. To overcome these two problems, we introduce a supervised machine learning based detection approach. To implement supervised machine learning, three steps are involved. First, features and target estimations are selected from malicious AODV behaviors in smart meter network to generate training data sets. Second, we assign a suitable classifier including support vector machine, k-nearest neighbors and decision trees to fit the training and predicted data. Third, we update our training data to maintain a dynamic threshold. Simulations are conducted using Python3.6 to evaluate the accuracy and the time overhead of our proposed supervised machine learning model. The simulation results show that the decision trees algorithm assures 100% accuracy with minimum time overhead to detect routing attacks in AODV.","PeriodicalId":150308,"journal":{"name":"Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134131578","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: 3

A Time-aware Method for Occupancy Detection in a Building 建筑物占用检测的时间感知方法

Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China Pub Date : 1900-01-01 DOI: 10.4108/eai.29-6-2019.2282388

Ling Song, Xiaofei Niu, Qiang Lyu, Shunming Lyu, Tian Tian

{"title":"A Time-aware Method for Occupancy Detection in a Building","authors":"Ling Song, Xiaofei Niu, Qiang Lyu, Shunming Lyu, Tian Tian","doi":"10.4108/eai.29-6-2019.2282388","DOIUrl":"https://doi.org/10.4108/eai.29-6-2019.2282388","url":null,"abstract":"The target of buildings’ energy efficient is to facilitate a comfortable environment for occupants while maintaining minimal energy consumption. Occupant behaviors pay a large impact in influencing the energy consumption. Time-aware occupancy detection could give information support for intelligent building energy management. In this paper several building occupancy detection methods, which are based on the temporal analysis of historical data, are proposed for providing different size of prediction window occupancy detection. Each proposed approaches are evaluated against accurate real-life data collected from a building. Experiments have been conducted using actual occupancy data under six different time horizons can be used to perform time-aware occupancy states prediction. The experimental results show that Stochastic Gradient Descent (SGD) and Gaussian mixture models-Hidden Markov Model (GMM-HMM) outperforms the other methods for the evaluation. With proposed more accurate time-aware occupancy prediction algorithms, we hope to develop more energy-efficient HVAC(Heating, Ventilation, and Air Conditioning) scheduling systems in order to save energy consumption.","PeriodicalId":150308,"journal":{"name":"Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123649862","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

A Social Network Information Dissemination Model Based on Evolutionary Game Considering Node’s Attitude 考虑节点态度的进化博弈社会网络信息传播模型

Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China Pub Date : 1900-01-01 DOI: 10.4108/eai.29-6-2019.2282003

Hongcheng Huang, Licheng Lai, Min Hu, Mengyuan Dong, Tingting Wang

{"title":"A Social Network Information Dissemination Model Based on Evolutionary Game Considering Node’s Attitude","authors":"Hongcheng Huang, Licheng Lai, Min Hu, Mengyuan Dong, Tingting Wang","doi":"10.4108/eai.29-6-2019.2282003","DOIUrl":"https://doi.org/10.4108/eai.29-6-2019.2282003","url":null,"abstract":"As a kind of social attribute of bounded rational users, attitude continuously selects and updates in the process of interaction between nodes, which makes the behavioral game between communication subjects and affects the dissemination of information. To analyze the impact of attitude changes on information, this paper proposes an information propagation model based on evolutionary game. Firstly, from the individual point of view, the update rules of the node's attitude are defined according to non-Bayesian social learning rules. Secondly, the game matrix between nodes based on attitude value is established, and the information dissemination model based on node attitude is established according to the evolutionary analysis paradigm. By replicating the equilibrium solution of dynamic equations with both positive and negative attitudes, and analyzing the stability of the corresponding equilibrium points, the evolution mechanism of dynamic interaction between attitude nodes is obtained. Finally, the impact of different attitudes on information dissemination was analyzed by combining SIS model. The validity of the proposed model is verified by numerical analysis and simulation experiments, and the simulation results show that the change of different attitude of nodes plays an important role in information dissemination.","PeriodicalId":150308,"journal":{"name":"Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129834978","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

A Information Propagation Model Based on Various Emotions and Heterogeneous Mean Field in Social Networks 社交网络中基于多种情绪和异构平均场的信息传播模型

Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China Pub Date : 1900-01-01 DOI: 10.4108/eai.29-6-2019.2282013

Tingting Wang, Min Hu, Lan Kou

{"title":"A Information Propagation Model Based on Various Emotions and Heterogeneous Mean Field in Social Networks","authors":"Tingting Wang, Min Hu, Lan Kou","doi":"10.4108/eai.29-6-2019.2282013","DOIUrl":"https://doi.org/10.4108/eai.29-6-2019.2282013","url":null,"abstract":"Information propagation in social networks can be effected by various factors, such as connected relationships, interactions between users, and so on. Previous studies mainly focused on analyzing the impact of physical connections on information propagation, and rarely studied the effects of different emotions on information propagation. Aiming to solve this problem, this paper proposes an emotion-based susceptible-infected-recovered information propagtion model(E-SIR). The model primarily researches the impacts of different emotions and diverse connections on the information propagtion process. We introduced the emotional transmissibility and the information transmissibility to describe the infection abilit ies of different emotions and the possibility of information transmission between different users,respectively. In addition, the dynamic equations are established based on the heterogeneous mean field. The burst threshold and spreading scale are theoretically analyzed and verified by experiments. In general, this paper focuses on the impacts of various emotions and different connections on information propagation.","PeriodicalId":150308,"journal":{"name":"Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129808886","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: 2

Harnessing D2D Communications in Collaborative Mobile Clouds for Content Sharing: An Energy Efficient Communication Scheme 在协作移动云中利用D2D通信进行内容共享:一种节能通信方案

Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China Pub Date : 1900-01-01 DOI: 10.4108/eai.29-6-2019.2282757

Jun Huang, Chao-Ying Huang, Cong-Cong Xing

引用次数: 0

A Hierarchical Bayesian Model for Matching Unlabeled Point Sets 无标记点集匹配的层次贝叶斯模型

Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China Pub Date : 1900-01-01 DOI: 10.4108/eai.29-6-2019.2282677

Xin Hu, Xiaodong Zhang, Xuequan Zhou, Hua Zhang, Chunshan Li, Deqiong Ding, Dianhui Chu

引用次数: 1

A Effective Feature Construction Method for Fall Detection using Smartphone 一种有效的智能手机跌倒检测特征构建方法

Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China Pub Date : 1900-01-01 DOI: 10.4108/eai.29-6-2019.2282809

Chunshan Li, Tianyu Dai, Dianhui Chu, Xiaodong Zhang

引用次数: 0

Trust prediction based on grey exponential smoothing method in VANETs 基于灰色指数平滑方法的VANETs信任预测

Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China Pub Date : 1900-01-01 DOI: 10.4108/eai.29-6-2019.2282065

Sanshun Zhang, Li Li, Hui Xia, Rui Zhang, Ye Li

引用次数: 0

Improved Capsule Network for Gaze Estimation in Wireless Sensor Networks 用于无线传感器网络注视估计的改进胶囊网络

Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China Pub Date : 1900-01-01 DOI: 10.4108/eai.29-6-2019.2282839

Mingyuan Luo, Xi Liu, Wei Wang, Wei Huang

引用次数: 1