检索结果-内蒙古大学图书馆

5th International Academic Exchange Conference on Science and Technology Innovation, IAECST 2023

作者： Wu, Yufeng Liu, Chengyu Guo, Wenjian Beijing University of Posts and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service Beijing China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing China

ISBN: (纸本)9798350357738

Since the Turing test, creating believable open-domain dialogues has been a basic problem in the study of artificial intelligence. Achieving success with dialogue models can greatly improve natural human-computer interactions and open up new possibilities for applications such as chatbots for therapy. Incorporating emotional information into dialogue systems and giving them personas can enhance user satisfaction by fostering more natural communication and human-like conversations. Both of these study directions are comparatively well-established, with important accomplishments in them. On the other hand, various roles in real-life discussion scenarios portray emotions in different ways. In order to create more fulfilling and human-like discussions, we investigate in this study the integration of personas and emotions in dialogue creation systems. Through the combination of explicit and implicit persons, we tackle the problem of individualized and emotional conversation. While implicit personas are gleaned from linguistic style, colloquial idioms, and personality attributes, explicit personas are derived from user profiles. Explicit personas and emotional labels are incorporated into the dialogue agent, and implicit personas are captured through the use of latent variables in a pre-trained Transformer model. Our suggested method enhances the authenticity of discussions and user experience by producing responses that are consistent with personas and emotions, hence improving the quality of communication. © 2023 IEEE.

关键词： Human computer interaction

来源：评论

学校读者我要写书评

暂无评论

LRChain:data protection and sharing method of learning archives based on consortium blockchain

引用

The Journal of China Universities of Posts and Telecommunications 2024年第4期31卷 28-42页

作者： Lan Lina Gao Yuhan Shi Ruisheng Wu Fenfen School of Humanities Beijing University of Posts and TelecommunicationsBeijing 100876China School of Cyberspace Security Beijing University of Posts and TelecommunicationsBeijing 100876China Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and TelecommunicationsMinistry of EducationBeijing 100876China

Learning archives management in traditional systems faces challenges such as inadequate security,weak tamper resistance,and limited sharing *** address these issues,this paper proposes LRChain,a method based on consortium blockchain,for lifelong learning archives data protection and *** employs a combination of on-chain and off-chain cooperative storage using a consortium chain and inter planetary file system(IPFS)to enhance data security and *** also enables fine-grained verification of learning archives through selective disclosure principles,ensuring privacy protection of sensitive ***,an attributebased encryption(ABE)algorithm is utilized to establish authorized access control for learning archives,facilitating safe and trusted *** evaluations and security analyses demonstrate that this method exhibits decentralization,strong security,tamper resistance,and performs well,effectively meeting the requirements for secure sharing of learning archive data.

关键词： learning archives consortium blockchain collaborative storage secure sharing

来源：评论

学校读者我要写书评

暂无评论

Enhanced mutual authentication model of IoT

引用

Journal of China Universities of Posts and Telecommunications 2013年第SUPPL -2期20卷 69-74页

作者： Yang, Jin-Cui Pang, Hao Zhang, Xin School of Software Engineering Beijing University of Posts and Telecommunications Beijing 100876 China Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing 100876 China Bank of Communications Beijing Branch Beijing 100032 China

The authentication mechanism of the Internet of things (IoT) control system is an important research field. This paper aims to give an appropriate authentication mechanism of IoT control system. It analyzes the pros and cons of some existing authentication mechanisms, proposes an enhanced bi-direction authentication mechanism for IoT control system, discusess the proposed mechanism in detail, including the improvements measures, the authentication process and the authentication model. Finally, this paper presents the security analysis of the enhanced authentication model. Analysis results indicate that the model is a relatively feasible security authentication model for the IoT control system. © 2013 The Journal of China Universities of Posts and Telecommunications.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Web Attack Detection through Network-Traffic-Based Feature Engineering and Machine Learning

Web Attack Detection through Network-Traffic-Based Feature E...

引用

2020 International Conference on Cyberspace Innovation of Advanced Technologies, CIAT 2020

作者： Yang, Jian Wang, Hao Lu, Yueming School of Cyberspace Security Key Lab of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781450387828

The design of feature set is a basic research direction of anomaly detection technology. The characterization ability of feature set directly affects the accuracy and generalization ability of intrusion detection algorithm. KDD CUP 99 is the most widely used data set in anomaly detection related research papers, but the feature set needs to analyze the payload content characteristics of packets, so the feature set cannot be applied to the encrypted traffic. CICIDS2017 is also a widely used data set. However, because data in PCAP format can only be used as input, the generalization ability of the model trained by this data set is poor when it is used for real-time attack detection. Based on the above problems, a feature set based on network flow characteristics is designed and implemented in this paper, which includes the time-window-based statistical features related to network traffic and host-related statistical features. Experiments show that the anomaly detection model trained by the feature set can meet the requirements of both real-time and classification accuracy. © 2020 ACM.

关键词： Intrusion detection

来源：评论

学校读者我要写书评

暂无评论

A recommend system for modelling large-scale advertising

A recommend system for modelling large-scale advertising

引用

International Conference on Cyberspace Technology, CCT 2014

作者： Ma, Jing Lu, Yueming School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Key Laboratory of Trustworthy Distributed Computing and Service BUPT Ministry of Education Beijing China

ISBN: (纸本)9781849199285

In a large-scale network environment, the Internet has produced an amount of digital information such as social media, e-commercial comments, online shopping records and advertising click logs. So, recommend systems not only furnish users with satisfied requirements but also bring about healthy profit to companies. To cope with massive data, we proposed an effective recommend system (ERS) for modelling abundant history data. Firstly, we advise a new data split strategy to make the recommend system fit for large scale advertising. Then, a distributed-recommendation algorithm is designed. Finally, we apply ERS and distributed computing and storage tools (such as Spark, Hadoop, etc.) to model history data aiming at improving the system efficiency. In this paper, we also compare and analyse diverse performances of ERS including its efficiency and its accuracy.

关键词： Metadata

来源：评论

学校读者我要写书评

暂无评论

Multi-source and multi-dimensional network security situational awareness model

Multi-source and multi-dimensional network security situatio...

引用

2020 International Conference on Cyberspace Innovation of Advanced Technologies, CIAT 2020

作者： Lv, Luqin Lu, Yueming School of Cyberspace Security Key Lab of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781450387828

Aiming at the problem that single protection technology is difficult to meet the needs of network security, the rationality and accuracy of situation assessment index are poor, the multi-source and multi-dimensional network security situation awareness model and multi-source data association analysis method are proposed. This model combines with data acquisition, data preprocessing, abnormal analysis, security threat assessment and situation visualization. By using Apriori algorithm to mine the relationship between multiple sources of data, the strong rules are filtered out. The experimental results show that the model can accurately perceive known intrusion, unknown threat and its own vulnerability. © 2020 ACM.

关键词： Visualization

来源：评论

学校读者我要写书评

暂无评论

Reliability Measurement Of Vehicle Sensor Data Based On Historical Perception 9

Reliability Measurement Of Vehicle Sensor Data Based On Hist...

引用

9th IEEE International Conference on Data Science in Cyberspace, DSC 2024

作者： Guo, Chenqing Zuo, Jinxin Lu, Yueming Xie, Weixuan Beijing University of Posts and Telecommunications School of Cyberspace Security Key Lab of Trustworthy Distributed Computing and Service Ministry of Education Beijing China

ISBN: (纸本)9798350391367

On-board sensors are utilized for monitoring and collecting a diverse range of data pertaining to the vehicle and its surroundings. However, in the field of Internet of Vehicles, security threats encountered by vehicle sensors often result in compromised accuracy of collected data. Therefore, it is crucial to investigate trusted measurement methods for vehicle sensor data. This paper proposes a reliable measurement approach for vehicle sensor data based on historical perception. The method initially achieves historical feature extraction through time correlation of single sensor sequence data and spatial correlation of multisensor data. Subsequently, a reliability measurement method is devised to quantify real-time data reliability by assessing the deviation from the theoretical expected value. Finally, historical data reliability is integrated with real-time data reliability to enhance accuracy of the overall reliability measurement process. This approach takes into consideration spatio-temporal correlation of vehicle sensor data and resolves issues stemming from unbalanced datasets that lead to inaccurate evaluation results. Experimental findings demonstrate an accuracy rate of 98.91% for the proposed method. © 2024 IEEE.

关键词： Spatio-temporal data

来源：评论

学校读者我要写书评

暂无评论

Chinese Open Relation Extraction with Pointer-Generator Networks

Chinese Open Relation Extraction with Pointer-Generator Netw...

引用

IEEE International Conference on Data Science in Cyberspace (DSC)

作者： Ziheng Cheng Xu Wu Xiaqing Xie Jingchen Wu Ministry of Education Key Laboratory of Trustworthy Distributed Computing and Service

ISBN: (数字)9781728195582

ISBN: (纸本)9781728195599

Most of the traditional Chinese open relation extraction (Open RE) system exploit the syntactic, lexical and other language structure information obtained by natural language processing (NLP) tools from sentences to build hand-crafted patterns for extraction, which is easy to cause error propagation and affect the accuracy of extraction. In this paper, we propose an end-to-end abstract Chinese Open RE model based on the Pointer-Generator network, PGCORE. We employ the results extracted by the state-of-the-art pattern-based Chinese Open RE system as the training set of the model. Experimental results show that our method is outperforms the pattern-based several baselines system, which proves the feasibility and effectiveness of using deep learning models for Chinese Open RE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A method based on MD5 and time for preventing deception in electronic commerce

A method based on MD5 and time for preventing deception in e...

引用

International Conference on Cyberspace Technology, CCT 2014

作者： Hu, Zhenggang Lu, Yueming School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Key Laboratory of Trustworthy Distributed Computing and Service BUPT Ministry of Education Beijing China

ISBN: (纸本)9781849199285

Aiming at reducing the risk of data being intercepted and preventing deceptions in the electronic commerce, this paper proposes a method based on MD5 and time which can effectively prevent the deception in data transmission. The method uses the traditional MD5 algorithm to encrypt and validate important data, then verifying the validity and legitimacy of the data by using time.

关键词： Electronic commerce MD5 algorithm Preventing deception Time

来源：评论

学校读者我要写书评

暂无评论

A tensor-based sub-mode coordinate algorithm for stock prediction 3

A tensor-based sub-mode coordinate algorithm for stock predi...

引用

3rd IEEE International Conference on Data Science in Cyberspace, DSC 2018

作者： Huang, Jieyun Zhang, Yunjia Zhang, Jialai Zhang, Xi Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing China School of Electronic Information Sichuan University Chengdu China

ISBN: (纸本)9781538642108

The investment on the stock market is prone to be affected by the Internet. For the purpose of improving the prediction accuracy, we propose a multi-task stock prediction model that not only considers the stock correlations but also supports multi-source data fusion. Our proposed model first utilizes tensor to integrate the multi-sourced data, including financial Web news, investors' sentiments extracted from the social network and some quantitative data on stocks. In this way, the intrinsic relationships among different information sources can be captured, and meanwhile, multi-sourced information can be complemented to solve the data sparsity problem. Secondly, we propose an improved sub-mode coordinate algorithm (SMC). SMC is based on the stock similarity, aiming to reduce the variance of their subspace in each dimension produced by the tensor decomposition. The algorithm is able to improve the quality of the input features, and thus improves the prediction accuracy. And the paper utilizes the Long Short-Term Memory (LSTM) neural network model to predict the stock fluctuation trends. Finally, the experiments on 78 A-share stocks in CSI 100 and thirteen popular HK stocks in the year 2015 and 2016 are conducted. The results demonstrate the improvement on the prediction accuracy and the effectiveness of the proposed model. © 2018 IEEE.

关键词： Tensors

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：