Pub Date : 2021-10-01DOI: 10.1109/NaNA53684.2021.00031
Jingping She, Ne Wang, Ruiting Zhou, Chen Tian
Compared with traditional cloud computing, edge-cloud computing brings many benefits, such as low latency, low bandwidth cost, and high security. Thanks to these advantages, a large number of distributed machine learning (ML) jobs are trained on the edge-cloud network to support smart applications, adopting the parameter server (PS) architecture. The scheduling of such ML jobs needs to consider different data transmission delay and frequent communication between workers and PSs, which brings a fundamental challenge: how to deploy workers and PSs on edge-cloud networks for ML jobs to minimize the average job completion time. To solve this problem, we propose an online scheduling framework to determine the location and execution time window for each job upon its arrival. Our algorithm includes: (i) an online scheduling framework that groups unprocessed ML jobs iteratively into multiple batches; (ii) a batch scheduling algorithm that maximizes the number of scheduled jobs in the current batch; (iii) two greedy algorithms that deploy workers and PSs to minimize the deployment cost. Large-scale and trace-driven simulations show that our algorithm is superior to the most common and advanced schedulers in today’s cloud systems.
{"title":"Online Scheduling of Machine Learning Jobs in Edge-Cloud Networks","authors":"Jingping She, Ne Wang, Ruiting Zhou, Chen Tian","doi":"10.1109/NaNA53684.2021.00031","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00031","url":null,"abstract":"Compared with traditional cloud computing, edge-cloud computing brings many benefits, such as low latency, low bandwidth cost, and high security. Thanks to these advantages, a large number of distributed machine learning (ML) jobs are trained on the edge-cloud network to support smart applications, adopting the parameter server (PS) architecture. The scheduling of such ML jobs needs to consider different data transmission delay and frequent communication between workers and PSs, which brings a fundamental challenge: how to deploy workers and PSs on edge-cloud networks for ML jobs to minimize the average job completion time. To solve this problem, we propose an online scheduling framework to determine the location and execution time window for each job upon its arrival. Our algorithm includes: (i) an online scheduling framework that groups unprocessed ML jobs iteratively into multiple batches; (ii) a batch scheduling algorithm that maximizes the number of scheduled jobs in the current batch; (iii) two greedy algorithms that deploy workers and PSs to minimize the deployment cost. Large-scale and trace-driven simulations show that our algorithm is superior to the most common and advanced schedulers in today’s cloud systems.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114996857","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}
Pub Date : 2021-10-01DOI: 10.1109/NaNA53684.2021.00063
Yuanqing Liu, Ning Xi, Yongbo Zhi
Due to the widespread of Android apps in our daily life, vulnerable or malicious apps have become two major threats on clients’ privacy. Taint analysis is one of the most widely used approach for detecting information leakage by tracking sensitive flows through the apps in accord with specific taint propagation rules and predefined sensitive sources and sinks. However, most existing static taint analysis tools, including FlowDroid, IccTA, etc., neglect the semantics of detected flows, especially for conditional branch in apps, which may cause a precision loss in practical environment. In this paper, we propose NLEU, a semantic-based taint analysis approach to improve the precision of traditional flow tracking techniques, which introduce a new dimension of information, i.e., the program’s semantics, for vetting Android apps. At the same time, NLEU can eliminate the insensitive flows of flow tracking techniques. The NLP techniques are adopted to extract the program semantics from codes and their comments. Through the experiments and evaluations, the result show that NLEU can improve the overall performance effectively compared with the traditional tools.
{"title":"NLEU: A Semantic-based Taint Analysis for Vetting Apps in Android","authors":"Yuanqing Liu, Ning Xi, Yongbo Zhi","doi":"10.1109/NaNA53684.2021.00063","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00063","url":null,"abstract":"Due to the widespread of Android apps in our daily life, vulnerable or malicious apps have become two major threats on clients’ privacy. Taint analysis is one of the most widely used approach for detecting information leakage by tracking sensitive flows through the apps in accord with specific taint propagation rules and predefined sensitive sources and sinks. However, most existing static taint analysis tools, including FlowDroid, IccTA, etc., neglect the semantics of detected flows, especially for conditional branch in apps, which may cause a precision loss in practical environment. In this paper, we propose NLEU, a semantic-based taint analysis approach to improve the precision of traditional flow tracking techniques, which introduce a new dimension of information, i.e., the program’s semantics, for vetting Android apps. At the same time, NLEU can eliminate the insensitive flows of flow tracking techniques. The NLP techniques are adopted to extract the program semantics from codes and their comments. Through the experiments and evaluations, the result show that NLEU can improve the overall performance effectively compared with the traditional tools.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127244270","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}
Pub Date : 2021-10-01DOI: 10.1109/NaNA53684.2021.00050
Wen Wang, Yuejuan Liu, Shikai Shen
Photonic Crystal Fiber (PCF) is also called microstructure fiber. The PCF is filled with magnetic fluid, and the optical characteristics of the PCF can be tuned and sensed according to the adjustable characteristics of the refractive index of the magnetic fluid. In this paper, the influence of filling magnetic fluid (MF) on the transmission characteristics of the PCF is analyzed. Precisely, PCF mode field distribution, fundamental mode refractive index and loss characteristics were analyzed. Analyze the influence of temperature on the transmission characteristics of two types of PCFs. The simulation results showed that the mode field area of the circular holes PCF is about twice that of the elliptical holes PCF under the condition of 20°C. With the increase of temperature, the loss peaks of elliptical holes PCF and circular holes PCF both increase and redshift. The wavelength sensitivity and loss sensitivity of the circular holes PCF are higher than that of the elliptical holes PCF. This work provides a reference for designing high-sensitivity optical fiber sensor devices.
{"title":"Transmission Characteristics of Photonic Crystal Fiber Filled with Magnetic Fluid","authors":"Wen Wang, Yuejuan Liu, Shikai Shen","doi":"10.1109/NaNA53684.2021.00050","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00050","url":null,"abstract":"Photonic Crystal Fiber (PCF) is also called microstructure fiber. The PCF is filled with magnetic fluid, and the optical characteristics of the PCF can be tuned and sensed according to the adjustable characteristics of the refractive index of the magnetic fluid. In this paper, the influence of filling magnetic fluid (MF) on the transmission characteristics of the PCF is analyzed. Precisely, PCF mode field distribution, fundamental mode refractive index and loss characteristics were analyzed. Analyze the influence of temperature on the transmission characteristics of two types of PCFs. The simulation results showed that the mode field area of the circular holes PCF is about twice that of the elliptical holes PCF under the condition of 20°C. With the increase of temperature, the loss peaks of elliptical holes PCF and circular holes PCF both increase and redshift. The wavelength sensitivity and loss sensitivity of the circular holes PCF are higher than that of the elliptical holes PCF. This work provides a reference for designing high-sensitivity optical fiber sensor devices.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125169985","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}
Pub Date : 2021-10-01DOI: 10.1109/NaNA53684.2021.00094
Mingyi You, Binhua Shi, Yunxia Ye, Kai Huang
Correct phase ambiguity resolution (CPAR) for a uniform circular array (UCA) phase interferometer is formally defined and some theoretic results for CPAR are derived. The probability of CPAR is numerically investigated considering the impact of baseline formulation, number of elements, radius wavelength ratio and phase measuring mechanism. Three methods for improving the probability of CPAR are proposed based on the findings of the characteristics of UCA phase interferometers. An extensive numerical investigation is conducted to validate the effectiveness of the proposed methods. The investigation results validate the effectiveness of the proposed methods and suggest choosing among the three proposed methods by considering the specific needs and engineering limitations.
{"title":"Characterizing and Improving the Probability of Correct Phase Ambiguity Resolution for Uniform Circular Array Phase Interferometers","authors":"Mingyi You, Binhua Shi, Yunxia Ye, Kai Huang","doi":"10.1109/NaNA53684.2021.00094","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00094","url":null,"abstract":"Correct phase ambiguity resolution (CPAR) for a uniform circular array (UCA) phase interferometer is formally defined and some theoretic results for CPAR are derived. The probability of CPAR is numerically investigated considering the impact of baseline formulation, number of elements, radius wavelength ratio and phase measuring mechanism. Three methods for improving the probability of CPAR are proposed based on the findings of the characteristics of UCA phase interferometers. An extensive numerical investigation is conducted to validate the effectiveness of the proposed methods. The investigation results validate the effectiveness of the proposed methods and suggest choosing among the three proposed methods by considering the specific needs and engineering limitations.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"237 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123005256","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}
Pub Date : 2021-10-01DOI: 10.1109/NaNA53684.2021.00096
Wenjiang Ji, Jiangcheng Yang, Yichuan Wang, Lei Zhu, Yuan Qiu, Xinhong Hei
Driving safety is an essential prerequisite to the rapid development of autonomous trams. However, the relationship of driving risk factors is nonlinear, which makes modeling difficult. To improve the accuracy of driving risk prediction, a data driven approach based on Generative Adversarial Networks was proposed. First of all, a communication and alarming scenario of Vehicular Ad-hoc Networks was demonstrated, in which the original data sets can be collected and transmitted by the help of sensors and Road Side Units. Then the RFE feature selection algorithm was used to keep the key features. To deal the sample asymmetry problem, a DCGAN model was designed for sparse samples expansion. At last, the XGBoost algorithm was used to classification and output the risk prediction result. During the experiment implemented with the public and real data sets, the risk prediction accuracy of proposed approach can up to 97.24%, for which takes the advantages in generating of the sparse samples.
{"title":"A Driving Risk Prediction Approach Based on Generative Adversarial Networks and VANET for Autonomous Trams","authors":"Wenjiang Ji, Jiangcheng Yang, Yichuan Wang, Lei Zhu, Yuan Qiu, Xinhong Hei","doi":"10.1109/NaNA53684.2021.00096","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00096","url":null,"abstract":"Driving safety is an essential prerequisite to the rapid development of autonomous trams. However, the relationship of driving risk factors is nonlinear, which makes modeling difficult. To improve the accuracy of driving risk prediction, a data driven approach based on Generative Adversarial Networks was proposed. First of all, a communication and alarming scenario of Vehicular Ad-hoc Networks was demonstrated, in which the original data sets can be collected and transmitted by the help of sensors and Road Side Units. Then the RFE feature selection algorithm was used to keep the key features. To deal the sample asymmetry problem, a DCGAN model was designed for sparse samples expansion. At last, the XGBoost algorithm was used to classification and output the risk prediction result. During the experiment implemented with the public and real data sets, the risk prediction accuracy of proposed approach can up to 97.24%, for which takes the advantages in generating of the sparse samples.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128646901","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}
Pub Date : 2021-10-01DOI: 10.1109/NaNA53684.2021.00015
Xufei Li, Shuiguang Zeng, Yangyang Liu
The open nature of wireless communication makes it facing variable interferences, the one by malicious attackers can be more harmful since they can choose worthful messages to interfere for benefit maximization. Such targeted messages generally require comprehensive protection by variable security mechanisms, which improve security in some sense as well as the risk of being selective attacked. One is the authentication mechanism that guarantees authenticity but suffers from length detection since the common authentication is conducted by appending digital signature bits to message. Due to this disadvantage, in this paper, we consider embedding the digital signature into the message at the physical layer, which is difficult to be sensed by attackers. Unlike the previous radio frequency (RF) watermark technique that adds low-power authentication tag symbols to base message symbols, while performing obvious constellation characteristics that still can be detected, to make the authentication tag non-perceptible to attackers, we propose to use Trellis coded modulation (TCM) in the embedding process to prevent constellation characteristics based detection. The accuracy of such an authentication scheme and its effect on the based messages are demonstrated by simulations. Simulation results show that the proposed method can greatly provide covert authentication while satisfying good authentication accuracy.
{"title":"Covert Authentication at the Physical Layer","authors":"Xufei Li, Shuiguang Zeng, Yangyang Liu","doi":"10.1109/NaNA53684.2021.00015","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00015","url":null,"abstract":"The open nature of wireless communication makes it facing variable interferences, the one by malicious attackers can be more harmful since they can choose worthful messages to interfere for benefit maximization. Such targeted messages generally require comprehensive protection by variable security mechanisms, which improve security in some sense as well as the risk of being selective attacked. One is the authentication mechanism that guarantees authenticity but suffers from length detection since the common authentication is conducted by appending digital signature bits to message. Due to this disadvantage, in this paper, we consider embedding the digital signature into the message at the physical layer, which is difficult to be sensed by attackers. Unlike the previous radio frequency (RF) watermark technique that adds low-power authentication tag symbols to base message symbols, while performing obvious constellation characteristics that still can be detected, to make the authentication tag non-perceptible to attackers, we propose to use Trellis coded modulation (TCM) in the embedding process to prevent constellation characteristics based detection. The accuracy of such an authentication scheme and its effect on the based messages are demonstrated by simulations. Simulation results show that the proposed method can greatly provide covert authentication while satisfying good authentication accuracy.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121355232","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}
In recent years, the concept of UAV (Unmanned Aerial Vehicle) swarm has been proposed and developed, which effectively solves the shortcomings of relatively small payload and relatively weak information perception processing capability in a single UAV operation. The research and application of UAV swarm technology has become an important direction of the development of UAV technology. UAV swarm not only can effectively improve the load capacity and information processing capacity through close cooperation between single UAV, but also has a high “self-healing” ability and strong robustness. However, due to the limited computing resources and complex external environment of UAVs, UAV swarm are vulnerable to forgery attacks, man-in-the-middle attacks and reply attacks. It is necessary to establish an authentication scheme to ensure the legitimate and reliable identity of UAVs for data exchange and sharing. However, traditional authentication schemes based on username, password or dynamic key have lower security levels, while RSA authentication requires a long session key and cannot meet the lightweight requirements in an UAV swarm. Based on the analysis and summary of existing authentication technologies and the special requirements of UAV swarm for cyber security, this paper puts forward an authentication scheme based on Zero Trust, achieves rapid authentication of UAV swarm in data exchange and sharing, and strengthens its ability to respond to cyber attacks.
{"title":"An efficient authentication scheme based on Zero Trust for UAV swarm","authors":"Dongyu Yang, Yue Zhao, Kaijun Wu, Xiaoyu Guo, Haiyang Peng","doi":"10.1109/NaNA53684.2021.00068","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00068","url":null,"abstract":"In recent years, the concept of UAV (Unmanned Aerial Vehicle) swarm has been proposed and developed, which effectively solves the shortcomings of relatively small payload and relatively weak information perception processing capability in a single UAV operation. The research and application of UAV swarm technology has become an important direction of the development of UAV technology. UAV swarm not only can effectively improve the load capacity and information processing capacity through close cooperation between single UAV, but also has a high “self-healing” ability and strong robustness. However, due to the limited computing resources and complex external environment of UAVs, UAV swarm are vulnerable to forgery attacks, man-in-the-middle attacks and reply attacks. It is necessary to establish an authentication scheme to ensure the legitimate and reliable identity of UAVs for data exchange and sharing. However, traditional authentication schemes based on username, password or dynamic key have lower security levels, while RSA authentication requires a long session key and cannot meet the lightweight requirements in an UAV swarm. Based on the analysis and summary of existing authentication technologies and the special requirements of UAV swarm for cyber security, this paper puts forward an authentication scheme based on Zero Trust, achieves rapid authentication of UAV swarm in data exchange and sharing, and strengthens its ability to respond to cyber attacks.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132529490","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}
Pub Date : 2021-10-01DOI: 10.1109/NaNA53684.2021.00093
Yongchao Dang, Chafika Benzaïd, Bin Yang, T. Taleb
Cellular-based Unmanned Aerial Vehicle (UAV) systems are a promising paradigm to provide reliable and fast Beyond Visual Line of Sight (BVLoS) communication services for UAV operations. However, such systems are facing a serious GPS spoofing threat for UAV’s position. To enable safe and secure UAV navigation BVLoS, this paper proposes a cellular network assisted UAV position monitoring and anti-GPS spoofing system, where deep learning approach is used to live detect spoofed GPS positions. Specifically, the proposed system introduces a MultiLayer Perceptron (MLP) model which is trained on the statistical properties of path loss measurements collected from nearby base stations to decide the authenticity of the GPS position. Experiment results indicate the accuracy rate of detecting GPS spoofing under our proposed approach is more than 93% with three base stations and it can also reach 80% with only one base station.
{"title":"Deep Learning for GPS Spoofing Detection in Cellular-Enabled UAV Systems","authors":"Yongchao Dang, Chafika Benzaïd, Bin Yang, T. Taleb","doi":"10.1109/NaNA53684.2021.00093","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00093","url":null,"abstract":"Cellular-based Unmanned Aerial Vehicle (UAV) systems are a promising paradigm to provide reliable and fast Beyond Visual Line of Sight (BVLoS) communication services for UAV operations. However, such systems are facing a serious GPS spoofing threat for UAV’s position. To enable safe and secure UAV navigation BVLoS, this paper proposes a cellular network assisted UAV position monitoring and anti-GPS spoofing system, where deep learning approach is used to live detect spoofed GPS positions. Specifically, the proposed system introduces a MultiLayer Perceptron (MLP) model which is trained on the statistical properties of path loss measurements collected from nearby base stations to decide the authenticity of the GPS position. Experiment results indicate the accuracy rate of detecting GPS spoofing under our proposed approach is more than 93% with three base stations and it can also reach 80% with only one base station.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134608838","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}
Pub Date : 2021-10-01DOI: 10.1109/NaNA53684.2021.00047
Zhi Qiao, Bo Liu, Bo Tian, Yu Liu
Network analysis is an unavoidable topic in data mining today, and network embedding is an important means to help solve network analysis. With the increasing of network data volume, the content is increasingly complicated, the embedding scenario of homogeneous graph has been gradually replaced by heterogeneous graph. More and more embedding algorithms for heterogeneous graphs are proposed. Heterogeneous network can naturally integrate different aspects of information, so heterogeneous network embedding is a relatively effective method to solve the diversity of big data. It is helpful in the areas of anomaly detection, user clustering and intent recommendation. Here we propose a Siamese Neural Network optimization method based on event relations and meta graphs. This method ensures the semantic integrity and event integrity of heterogeneous graphs by using events and meta graphs respectively. Then put the graph information in Triplet Network for training, and the embedding results are produced. A classification task on a dataset for the true network are designed to prove the method. A real network data set classification task is designed to prove that this method is helpful for heterogeneous graph analysis.
{"title":"Heterogeneous Network Embedding With Enhanced Event Awareness Via Triplet Network","authors":"Zhi Qiao, Bo Liu, Bo Tian, Yu Liu","doi":"10.1109/NaNA53684.2021.00047","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00047","url":null,"abstract":"Network analysis is an unavoidable topic in data mining today, and network embedding is an important means to help solve network analysis. With the increasing of network data volume, the content is increasingly complicated, the embedding scenario of homogeneous graph has been gradually replaced by heterogeneous graph. More and more embedding algorithms for heterogeneous graphs are proposed. Heterogeneous network can naturally integrate different aspects of information, so heterogeneous network embedding is a relatively effective method to solve the diversity of big data. It is helpful in the areas of anomaly detection, user clustering and intent recommendation. Here we propose a Siamese Neural Network optimization method based on event relations and meta graphs. This method ensures the semantic integrity and event integrity of heterogeneous graphs by using events and meta graphs respectively. Then put the graph information in Triplet Network for training, and the embedding results are produced. A classification task on a dataset for the true network are designed to prove the method. A real network data set classification task is designed to prove that this method is helpful for heterogeneous graph analysis.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117353427","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}
Pub Date : 2021-10-01DOI: 10.1109/NaNA53684.2021.00079
Xiaoyan Zhu, Y. Zhang, Lei Zhu, Xinhong Hei, Yichuan Wang, Feixiong Hu, Yanni Yao
As the mobile Internet is developing rapidly, people who use cell phones to access the Internet dominate, and the mobile Internet has changed the development environment of online public opinion and made online public opinion events spread more widely. In the online environment, any kind of public issues may become a trigger for the generation of public opinion and thus need to be controlled for network supervision. The method in this paper can identify entities from the event texts obtained from mobile Today's Headlines, People's Daily, etc., and informatize security of public opinion in event instances, thus strengthening network supervision and control in mobile, and providing sufficient support for national security event management. In this paper, we present a SW-BiLSTM-CRF model, as well as a model combining the RoBERTa pre-trained model with the classical neural network BiLSTM model. Our experiments show that this approach provided achieves quite good results on Chinese emergency corpus, with accuracy and F1 values of 87.21% and 78.78%, respectively.
{"title":"Chinese named entity recognition method for the field of network security based on RoBERTa","authors":"Xiaoyan Zhu, Y. Zhang, Lei Zhu, Xinhong Hei, Yichuan Wang, Feixiong Hu, Yanni Yao","doi":"10.1109/NaNA53684.2021.00079","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00079","url":null,"abstract":"As the mobile Internet is developing rapidly, people who use cell phones to access the Internet dominate, and the mobile Internet has changed the development environment of online public opinion and made online public opinion events spread more widely. In the online environment, any kind of public issues may become a trigger for the generation of public opinion and thus need to be controlled for network supervision. The method in this paper can identify entities from the event texts obtained from mobile Today's Headlines, People's Daily, etc., and informatize security of public opinion in event instances, thus strengthening network supervision and control in mobile, and providing sufficient support for national security event management. In this paper, we present a SW-BiLSTM-CRF model, as well as a model combining the RoBERTa pre-trained model with the classical neural network BiLSTM model. Our experiments show that this approach provided achieves quite good results on Chinese emergency corpus, with accuracy and F1 values of 87.21% and 78.78%, respectively.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129873504","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：