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2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)最新文献

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Encrypted Traffic Protocol Identification Based on Temporal and Spatial Features 基于时空特征的加密流量协议识别
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212827
Peng Zhu, G. Wang, Jing He, Yu Chang, Lingfei Kong, Jiewei Liu
{"title":"Encrypted Traffic Protocol Identification Based on Temporal and Spatial Features","authors":"Peng Zhu, G. Wang, Jing He, Yu Chang, Lingfei Kong, Jiewei Liu","doi":"10.1109/AINIT59027.2023.10212827","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212827","url":null,"abstract":"Cryptographic technology is the foundation and key to securing cyberspace, but there are still widespread cases of non-compliance and incorrectness in cryptographic applications, especially commercial cryptographic applications, etc. Detecting the compliance of encryption protocol cipher suites is an important part of carrying out cryptographic evaluation. Aiming at the difficult problems such as insufficient and insignificant extraction of encrypted traffic protocol features and poor effect of encrypted traffic protocol identification model, the concept of network traffic temporal relationship is invoked to comprehensively extract and learn the encrypted traffic protocol temporal features and control the redundant feature weights to highlight the key features in order to improve the identification accuracy. Through comparative experiments, we analyze the influence of temporal and spatial features on recognition effect, fuse spatio-temporal features of traffic, and propose a Transformer and Attention_CNN (TAC) fusion model of encrypted traffic protocol recognition to solve the problem of low accuracy of single feature recognition. The experimental results show that the proposed scheme can effectively distinguish various network protocols and accomplish the purpose of verifying the compliance of cipher suites in encryption protocols.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115403039","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 Sentence-BERT-based Model for Expressing Key Features of Hospital Web Logs 基于句子bert的医院网络日志关键特征表达模型
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212603
Tao Yang, MingYang Li, H. Deng, Junxiang Wang
{"title":"A Sentence-BERT-based Model for Expressing Key Features of Hospital Web Logs","authors":"Tao Yang, MingYang Li, H. Deng, Junxiang Wang","doi":"10.1109/AINIT59027.2023.10212603","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212603","url":null,"abstract":"Hospital web application log data contains a significant number of specialized terms, and there is a high degree of similarity in their expressions and content. This similarity often leads to a high false alarm rate in hospital network security detection. In this paper, we propose a SB-KFR model (Sentence-BERT-based Key Feature Representation) to tackle this problem. This model converts hospital web logs into feature vectors by extracting key features and performing vector transformation. In this paper, seven machine learning models are used to verify the feature vector. The experimental results demonstrate a reduction in false positives for hospital web application intrusion detection after applying the SB-KFR model to process the web logs.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125566172","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 Secure and Effective Authentication Method in 5G 一种安全有效的5G认证方法
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212595
XinJian Li, ChengTao Wang, Xinhao Zou, Shijun Wang
{"title":"A Secure and Effective Authentication Method in 5G","authors":"XinJian Li, ChengTao Wang, Xinhao Zou, Shijun Wang","doi":"10.1109/AINIT59027.2023.10212595","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212595","url":null,"abstract":"The 5th generation mobile networks (5G), as a key infrastructure in the digital society, are accelerating their standardization and commercialization processes globally. At the same time, 5G network security issues have also attracted unprecedented attention. The 5G network adopts a more open network architecture and a more flexible protocol system, and the openness and flexibility make the 5G network face new security challenges. Throughout the various security issues in mobile communication systems over time, protocol flaws have always been one of the most easily exploited vulnerabilities by attackers. Therefore, this article proposes a secure and effective protocol in 5G. The proposed scheme can resist multiple common attacks and provide perfect forward confidentiality. The security and performance analysis of the scheme shows that the protocol has good execution efficiency while ensuring the authentication process and subsequent communication security, which can balance efficiency and security.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"177 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122092882","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
Cross-Domain Data Link Security Portrait Based Attack Traceability Correlation 基于跨域数据链路安全画像的攻击可追溯性关联
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212474
Jianqian Sheng, Yuan Fang, Guannan Zhang, Xin Ding
{"title":"Cross-Domain Data Link Security Portrait Based Attack Traceability Correlation","authors":"Jianqian Sheng, Yuan Fang, Guannan Zhang, Xin Ding","doi":"10.1109/AINIT59027.2023.10212474","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212474","url":null,"abstract":"To address the problem of attackers invading the power system through cross-domain attacks and vulnerability exploitation, current research is focusing on security portrait technology. By creating a security portrait of the power system, real-time supervision and comprehensive understanding of abnormal user behavior can be achieved. However, traditional network traffic anomaly detection methods based on clustering analysis often have low accuracy. This article proposes an improved k-means clustering-based traffic anomaly detection method, which improves the efficiency and accuracy of constructing security portraits based on abnormal traffic. Secondly, the Yen's shortest path algorithm is used to select the optimal set in the path to determine the network attack path location, and finally, the attack traceability correlation of cross-domain data link security portraits is achieved, improving the recognition efficiency to 91.7% on the original basis.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128355871","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
The SG-CIM Entity Linking Method Based on BERT and Entity Name Embeddings 基于BERT和实体名称嵌入的SG-CIM实体链接方法
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212510
Xiaoqi Liao, Yufei Li, Yiwei Lou, Xinliang Ge, Shijie Gao, Pan Sun
{"title":"The SG-CIM Entity Linking Method Based on BERT and Entity Name Embeddings","authors":"Xiaoqi Liao, Yufei Li, Yiwei Lou, Xinliang Ge, Shijie Gao, Pan Sun","doi":"10.1109/AINIT59027.2023.10212510","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212510","url":null,"abstract":"The current iteration of the SG-CIM (State Grid Common Information Model) requires manual extraction of entity attributes from texts such as design plans and reports. To address the problems of slow update time and the high error rate of manual iteration data, this paper presents an entity linking method combing deep learning and knowledge base. Firstly, the SG-CIM model is used to construct a knowledge base of grid data used as a vector embedding of entities; Secondly, the joint recognition model of BERT-CRF and BERT-ENE(BERT-Entity Name Embeddings) is used for named entity recognition, where the BERT-ENE model can be used for dictionary matching of entity descriptions in the knowledge base; Then BERT-based binary classification model to predict the candidate entities, select the entity with the highest probability as the result, realize the entity disambiguation of alternate entities and new entities; Finally add the found important new entities to the SG-CIM model to realize the automated iteration of SG-CIM model. According to the experimental findings, the Entity Linking approaches have an F1-score of over 80%.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129310007","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
An Industrial-grade Solution for Convolutional Neural Network Optimization and Deployment 卷积神经网络优化与部署的工业级解决方案
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212632
Xinchao Wang, Yongxin Wang, Juan Li
{"title":"An Industrial-grade Solution for Convolutional Neural Network Optimization and Deployment","authors":"Xinchao Wang, Yongxin Wang, Juan Li","doi":"10.1109/AINIT59027.2023.10212632","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212632","url":null,"abstract":"The deployment of deep learning models into practical production applications has become increasingly important with the rapid development of deep learning in theoretical research. Currently, the deployment of deep learning models faces numerous challenges due to the increasingly large scale and computational requirements of these models, along with the limited storage and computing resources of mobile devices. This paper proposes a high-performance and versatile solution to address the challenges of practical model deployment. This study significantly enhances model inference speed by employing techniques such as DepGraph model pruning, operator fusion, and the NCNN inference framework while reducing the model size and storage overhead.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124079411","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
Cross-age face recognition for face images in digital archives 数字档案中人脸图像的跨年龄识别
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212553
Yinxue Wang, Shiqing Bai, Xueyu Wan, Fangyan Chen
{"title":"Cross-age face recognition for face images in digital archives","authors":"Yinxue Wang, Shiqing Bai, Xueyu Wan, Fangyan Chen","doi":"10.1109/AINIT59027.2023.10212553","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212553","url":null,"abstract":"Face images in digital archives have a large age span and suffer from varying degrees of image degradation over time, leading to a significant degradation in the performance of generic face recognition models. To address the above problems, this paper proposed an anti-noise cross-age face recognition model. The model combines local residual learning and soft thresholding module, then embeds them into the backbone network to remove irrelevant features and guide the network to extract valid initial facial features. In this case, the soft thresholding module adaptively sets thresholds by branching at two different scales. The initial facial features are decomposed into age-related features and identity-related features. The identity-related features are used for face recognition. Meanwhile, a benchmark test dataset based on real archives was constructed in this paper. The study shows that the model has a high degree of robustness and anti-noise interference. Also, soft thresholding has a positive impact on noise suppression.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126425445","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 process Fault Detection method Based on PCA and linear regression 基于主成分分析和线性回归的过程故障检测方法
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212532
Ce Han, Wei Chang, Feng Yuan, Kai Zhang
{"title":"A process Fault Detection method Based on PCA and linear regression","authors":"Ce Han, Wei Chang, Feng Yuan, Kai Zhang","doi":"10.1109/AINIT59027.2023.10212532","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212532","url":null,"abstract":"PCA is a common fault detection method, which has good performance in fault detection. But it is difficult to distinguish the specific fault location. This paper established a linear regression model through the measurement value of different points, and used R-squared to evaluate the model to eliminate models with poor fitting. In this paper, the above model was used to simulate the data set of Tennessee Eastman process, and some models obtained can detect the fault and reduce the range of failure. This paper provided a new fault detection method applied to train non-faulty samples.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115908968","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
Designing Data Permissions in the Enterprise Application Environment 企业应用环境中的数据权限设计
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212755
Ying Yuan, Xin Yi, Junbin ShangGuan
{"title":"Designing Data Permissions in the Enterprise Application Environment","authors":"Ying Yuan, Xin Yi, Junbin ShangGuan","doi":"10.1109/AINIT59027.2023.10212755","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212755","url":null,"abstract":"With the continuous improvement of social informationization, the digitalization of corporate construction is also developing comprehensively. Data, as a crucial source for creating wealth and competitive advantage, is undoubtedly the most significant asset for all enterprises. However, many companies face the dilemma of insufficient data granularity and configuration flexibility, which undermines the security and availability of their data assets. Therefore, this paper proposes an Api-based data permission control model (ADPC) based on the theoretical foundation of RBAC in the background of data application in the enterprise environment. Firstly, the model maps data objects to different levels of environmental variables in the corporate department structure, then flexibly authorizes and controls permissions through API configuration, and finally verifies its security with SQL AST. The ADPC model was implemented using the Spring Boot, Spring Security and MyBatis framework and was applied in a real enterprise environment. Through this approach, the ADPC model effectively addresses the limitations of traditional data permission control mechanisms in the enterprise application environment.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132057206","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
Physical layer key negotiation attacks and detection under a static environment 静态环境下物理层密钥协商攻击及检测
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212598
Y. Qi, Qiao Hu
{"title":"Physical layer key negotiation attacks and detection under a static environment","authors":"Y. Qi, Qiao Hu","doi":"10.1109/AINIT59027.2023.10212598","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212598","url":null,"abstract":"The existing physical layer key generation methods overly rely on the results of channel probing, which not only weakens the randomness of the key in a static environment but also makes the physical layer key vulnerable to active attacks. At the same time, in terms of defence technology, traditional physical layer intrusion detection methods mainly focus on the abnormal transmission of physical signals, making it difficult to identify potential key attack behaviours. This article proposes an attack method for the random operator-based key negotiation model in a static environment and then proposes a key attack detection scheme that utilizes the correlation between pilot signals and random signals for the above two attack behaviours. Under low false alarm rate conditions, this detection scheme has a higher detection rate compared to traditional physical layer intrusion detection methods.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115391716","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
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