The dark web is a shadow area hidden in the depths of the Internet,which is difficult to access through common search engines.Because of its anonymity,the dark web has gradually become a hotbed for a variety of cyber-...The dark web is a shadow area hidden in the depths of the Internet,which is difficult to access through common search engines.Because of its anonymity,the dark web has gradually become a hotbed for a variety of cyber-crimes.Although some research based on machine learning or deep learning has been shown to be effective in the task of analyzing dark web traffic in recent years,there are still pain points such as low accuracy,insufficient real-time performance,and limited application scenarios.Aiming at the difficulties faced by the existing automated dark web traffic analysis methods,a novel method named Dark-Forest to analyze the behavior of dark web traffic is proposed.In this method,firstly,particle swarm optimization algorithm is used to filter the redundant features of dark web traffic data,which can effectively shorten the training and inference time of the model to meet the realtime requirements of dark web detection task.Then,the selected features of traffic are analyzed and classified using the DeepForest model as a backbone classifier.The comparison experiment with the current mainstream methods shows that Dark-Forest takes into account the advantages of statistical machine learning and deep learning,and achieves an accuracy rate of 87.84%.This method not only outperforms baseline methods such as Random Forest,MLP,CNN,and the original DeepForest in both large-scale and small-scale dataset based learning tasks,but also can detect normal network traffic,tunnel network traffic and anonymous network traffic,which may close the gap between different network traffic analysis tasks.Thus,it has a wider application scenario and higher practical value.展开更多
现有的基于深度学习模型的词嵌入方法用于Web异常检测时,通常将语料库中没有出现的未知词汇(Out of Vocabulary,OOV)设置为unknown,并赋予零或随机向量输入到模型中进行训练,未考虑未知词汇在Web请求语句中的上下文关系。同时,在Web系...现有的基于深度学习模型的词嵌入方法用于Web异常检测时,通常将语料库中没有出现的未知词汇(Out of Vocabulary,OOV)设置为unknown,并赋予零或随机向量输入到模型中进行训练,未考虑未知词汇在Web请求语句中的上下文关系。同时,在Web系统代码开发过程中,基于个人习惯并为了增加代码的可读性,程序员设计的请求路径代码往往存在一定的模式。因此,考虑到Web请求的模式和单词语义间的相关性,研究基于Word2vec的动态未知词表示方法DUWe(Dynamic Unknown Word Embedding),该方法通过分析Web请求路径中单词上下文的关系来赋予未知词向量的表示内容。在CSIC-2010和WAF Dataset数据集上的实验评估表明,增加未知词表示方法比仅用Word2vec静态特征提取方法具有更好的性能,同时在准确性、精准率、召回率和F1-Score方面均有提高,在训练时间上最大降低1.14倍。展开更多
Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas...Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas become a focal point for contemporary researchers. Therefore, this paper aims to investigate the topologyoptimization of large cavity structures as a means to enhance their performance, safety, and efficiency. By usingthe variable density method, lightweight design is achieved without compromising structural strength. Theoptimization model considers both concentrated and distributed loads, and utilizes techniques like sensitivityfiltering and projection to obtain a robust optimized configuration. The mechanical properties are checked bycomparing the stress distribution and displacement of the unoptimized and optimized structures under the sameload. The results confirm that the optimized structures exhibit improved mechanical properties, thus offering keyinsights for engineering lightweight, high-strength large cavity structures.展开更多
本文介绍了ASP.NET Web API的主要特点及使用方法。在此基础上提出了自承载、跨域资源共享、Swagger文档管理、缓存、限流等增强和改进技术。接下来,又提出了针对大量API的接口管理需求及其技术实现方案。进一步地,提出这些技术的集成方...本文介绍了ASP.NET Web API的主要特点及使用方法。在此基础上提出了自承载、跨域资源共享、Swagger文档管理、缓存、限流等增强和改进技术。接下来,又提出了针对大量API的接口管理需求及其技术实现方案。进一步地,提出这些技术的集成方案,并应用于真实工业环境中,现场运行稳定,接口查看和调用方便,为业主创造了巨大经济效益。展开更多
This paper proposes a new approach for classification for query interfaces of Deep Web, which extracts features from the form＇s text data on the query interfaces, assisted with the synonym library, and uses radial ba...This paper proposes a new approach for classification for query interfaces of Deep Web, which extracts features from the form＇s text data on the query interfaces, assisted with the synonym library, and uses radial basic function neural network （RBFNN） algorithm to classify the query interfaces. The applied RBFNN is a kind of effective feed-forward artificial neural network, which has a simple networking structure but features with strength of excellent nonlinear approximation, fast convergence and global convergence. A TEL_8 query interfaces＇ data set from UIUC on-line database is used in our experiments, which consists of 477 query interfaces in 8 typical domains. Experimental results proved that the proposed approach can efficiently classify the query interfaces with an accuracy of 95.67%.展开更多
介绍了接口自动机的基本语法,针对目前最主要的一种描述和执行基于工作流模式的Web服务组合的规范——Web服务商业流程执行语言(business process execution language for Web services,BPEL4WS),定义了接口自动机和BPEL4WS之间的概念映...介绍了接口自动机的基本语法,针对目前最主要的一种描述和执行基于工作流模式的Web服务组合的规范——Web服务商业流程执行语言(business process execution language for Web services,BPEL4WS),定义了接口自动机和BPEL4WS之间的概念映射,并给出了BPEL4WS的基于接口自动机的形式化模型,最后通过一个案例给出了BPEL4WS到接口自动机的映射及验证的方法。展开更多
基金funded by Henan Provincial Key R&D and Promotion Special Project(Science and Technology Tackling)(212102210165)National Social Science Foun-dation Key Project(20AZD114)+1 种基金Henan Provincial Higher Education Key Research Project Program(20B520008)Public Security Behavior Scientific Research and Technological Innovation Project of the Chinese People’s Public Security University(2020SYS08).
文摘The dark web is a shadow area hidden in the depths of the Internet,which is difficult to access through common search engines.Because of its anonymity,the dark web has gradually become a hotbed for a variety of cyber-crimes.Although some research based on machine learning or deep learning has been shown to be effective in the task of analyzing dark web traffic in recent years,there are still pain points such as low accuracy,insufficient real-time performance,and limited application scenarios.Aiming at the difficulties faced by the existing automated dark web traffic analysis methods,a novel method named Dark-Forest to analyze the behavior of dark web traffic is proposed.In this method,firstly,particle swarm optimization algorithm is used to filter the redundant features of dark web traffic data,which can effectively shorten the training and inference time of the model to meet the realtime requirements of dark web detection task.Then,the selected features of traffic are analyzed and classified using the DeepForest model as a backbone classifier.The comparison experiment with the current mainstream methods shows that Dark-Forest takes into account the advantages of statistical machine learning and deep learning,and achieves an accuracy rate of 87.84%.This method not only outperforms baseline methods such as Random Forest,MLP,CNN,and the original DeepForest in both large-scale and small-scale dataset based learning tasks,but also can detect normal network traffic,tunnel network traffic and anonymous network traffic,which may close the gap between different network traffic analysis tasks.Thus,it has a wider application scenario and higher practical value.
文摘现有的基于深度学习模型的词嵌入方法用于Web异常检测时,通常将语料库中没有出现的未知词汇(Out of Vocabulary,OOV)设置为unknown,并赋予零或随机向量输入到模型中进行训练,未考虑未知词汇在Web请求语句中的上下文关系。同时,在Web系统代码开发过程中,基于个人习惯并为了增加代码的可读性,程序员设计的请求路径代码往往存在一定的模式。因此,考虑到Web请求的模式和单词语义间的相关性,研究基于Word2vec的动态未知词表示方法DUWe(Dynamic Unknown Word Embedding),该方法通过分析Web请求路径中单词上下文的关系来赋予未知词向量的表示内容。在CSIC-2010和WAF Dataset数据集上的实验评估表明,增加未知词表示方法比仅用Word2vec静态特征提取方法具有更好的性能,同时在准确性、精准率、召回率和F1-Score方面均有提高,在训练时间上最大降低1.14倍。
基金the National Natural Science Foundation of China and the Natural Science Foundation of Jiangsu Province.It was also supported in part by Young Elite Scientists Sponsorship Program by CAST.
文摘Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas become a focal point for contemporary researchers. Therefore, this paper aims to investigate the topologyoptimization of large cavity structures as a means to enhance their performance, safety, and efficiency. By usingthe variable density method, lightweight design is achieved without compromising structural strength. Theoptimization model considers both concentrated and distributed loads, and utilizes techniques like sensitivityfiltering and projection to obtain a robust optimized configuration. The mechanical properties are checked bycomparing the stress distribution and displacement of the unoptimized and optimized structures under the sameload. The results confirm that the optimized structures exhibit improved mechanical properties, thus offering keyinsights for engineering lightweight, high-strength large cavity structures.
文摘本文介绍了ASP.NET Web API的主要特点及使用方法。在此基础上提出了自承载、跨域资源共享、Swagger文档管理、缓存、限流等增强和改进技术。接下来,又提出了针对大量API的接口管理需求及其技术实现方案。进一步地,提出这些技术的集成方案,并应用于真实工业环境中,现场运行稳定,接口查看和调用方便,为业主创造了巨大经济效益。
基金Supported by the National Natural Science Foundation of China(60473045)the Research Plan of Hebei Province(05213573)the Research Plan of Education Office of Hebei Province(2004406).
文摘This paper proposes a new approach for classification for query interfaces of Deep Web, which extracts features from the form＇s text data on the query interfaces, assisted with the synonym library, and uses radial basic function neural network （RBFNN） algorithm to classify the query interfaces. The applied RBFNN is a kind of effective feed-forward artificial neural network, which has a simple networking structure but features with strength of excellent nonlinear approximation, fast convergence and global convergence. A TEL_8 query interfaces＇ data set from UIUC on-line database is used in our experiments, which consists of 477 query interfaces in 8 typical domains. Experimental results proved that the proposed approach can efficiently classify the query interfaces with an accuracy of 95.67%.
文摘介绍了接口自动机的基本语法,针对目前最主要的一种描述和执行基于工作流模式的Web服务组合的规范——Web服务商业流程执行语言(business process execution language for Web services,BPEL4WS),定义了接口自动机和BPEL4WS之间的概念映射,并给出了BPEL4WS的基于接口自动机的形式化模型,最后通过一个案例给出了BPEL4WS到接口自动机的映射及验证的方法。
