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Learning group interaction for sports video understanding from a perspective of athlete

Frontiers of computer Science 2024年第4期18卷 175-188页

作者： Rui HE Zehua FU Qingjie LIU Yunhong WANG Xunxun CHEN Intelligent Recognition and Image Processing(IRIP)Lab School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Hangzhou Innovation Institute Behang UniversityHangzhou 310051China National computer network emergency response technical team/coordination center of china(CNCERT or CNCERT/CC) Beijing 100029China

Learning activities interactions between small groups is a key step in understanding team sports *** research focusing on team sports videos can be strictly regarded from the perspective of the audience rather than the *** team sports videos such as volleyball and basketball videos,there are plenty of intra-team and inter-team *** this paper,a new task named Group Scene Graph Generation is introduced to better understand intra-team relations and inter-team relations in sports *** tackle this problem,a novel Hierarchical Relation network is *** all players in a video are finely divided into two teams,the feature of the two teams’activities and interactions will be enhanced by Graph Convolutional networks,which are finally recognized to generate Group Scene *** evaluation,built on Volleyball dataset with additional 9660 team activity labels,a Volleyball+dataset is proposed.A baseline is set for better comparison and our experimental results demonstrate the effectiveness of our ***,the idea of our method can be directly utilized in another video-based task,Group Activity *** show the priority of our method and display the link between the two ***,from the athlete’s view,we elaborately present an interpretation that shows how to utilize Group Scene Graph to analyze teams’activities and provide professional gaming suggestions.

关键词： group scene graph group activity recognition scene graph generation graph convolutional network sports video understanding

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Modeling and Performance Analysis of UAV-Aided Millimeter Wave Cellular networks with Stochastic Geometry

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china Communications 2024年第6期21卷 146-162页

作者： Li Junruo Wang Yuanjie Cui Qimei Hou Yanzhao Tao Xiaofeng National Engineering Laboratory for Mobile network Technologies Beijing University of Posts and TelecommunicationsBeijing 100876China National computer network emergency response technical team/coordination center of china(CNCERT/CC) Beijing 100029China Department of Broadband Communication Peng Cheng LaboratoryShenzhen 518055China

UAV-aided cellular networks,millimeter wave(mm-wave) communications and multi-antenna techniques are viewed as promising components of the solution for beyond-5G(B5G) and even 6G *** leveraging the power of stochastic geometry,this paper aims at providing an effective framework for modeling and analyzing a UAV-aided heterogeneous cellular network,where the terrestrial base stations(TBSs) and the UAV base stations(UBSs) coexist,and the UBSs are provided with mm-wave and multi-antenna *** modeling the TBSs as a PPP and the UBSs as a Matern hard-core point process of type Ⅱ(MPH-Ⅱ),approximated but accurate analytical results for the average rate of the typical user of both tiers are derived through an approximation method based on the mean interference-to-signal ratio(MISR) *** influence of some relevant parameters is discussed in detail,and some insights into the network deployment and optimization are *** results show that some trade-offs are worthy of being considered,such as the antenna array size,the altitude of the UAVs and the power control factor of the UBSs.

关键词： average rate downlink millimeter wave point process theory SIR stochastic geometry UAVaided cellular networks

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Distributed Region Tracking and Perimeter Surveillance for Second-Order Multi-Agent Systems in Star-Shaped Sets

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Journal of Systems Science & Complexity 2024年第5期37卷 1995-2020页

作者： SHANG Juan MO Lipo MI Rongxin CAO Xianbing School of Mathematics and Statistics Beijing Technology and Business University The Department of Foundation Shijiazhuang Institute of Railway Technology School of computer and Artificial Intelligence Beijing Technology and Business University Research Centre for Agri-Product Quality Traceability Beijing Technology and Business University coordination center of china National Computer Network Emergency Response Technical Team

This paper investigates region tracking and perimeter surveillance of second-order multi-agent systems, where all agents move within a star-shaped set. First, by coordination transformations,the region tracking problem is converted from the star-shaped sets to a circular region. The authors employ communication and collaboration to complete region tracking and perimeter surveillance tasks,and then revert back to the star-shaped set by using inverse transformations. Second, the authors propose a distributed control strategy based on attractive and interaction potential functions, under which all agents can quickly track a given circular region and move around the perimeter. Finally,the authors validate the effectiveness and performance advantages of the proposed method through simulation experiments.

关键词： Distributed control multi-agent systems star-shaped sets target tracking

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AWeb Application Fingerprint Recognition Method Based on Machine Learning

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computer Modeling in Engineering & Sciences 2024年第7期140卷 887-906页

作者： Yanmei Shi Wei Yu Yanxia Zhao Yungang Jia School of Integrated Circuit Science and Engineering Tianjin University of TechnologyTianjin300382China College of International Business Zhejiang Yuexiu UniversityShaoxing312030China School of Public Administration Zhejiang Gongshang UniversityHangzhou310018China Tianjin Branch of National computer network emergency response technical team/coordination center of china Tianjin300100China

Web application fingerprint recognition is an effective security technology designed to identify and classify web applications,thereby enhancing the detection of potential threats and *** fingerprint recognition methods,which rely on preannotated feature matching,face inherent limitations due to the ever-evolving nature and diverse landscape of web *** response to these challenges,this work proposes an innovative web application fingerprint recognition method founded on clustering *** method involves extensive data collection from the Tranco List,employing adjusted feature selection built upon Wappalyzer and noise reduction through truncated SVD dimensionality *** core of the methodology lies in the application of the unsupervised OPTICS clustering algorithm,eliminating the need for preannotated *** transforming web applications into feature vectors and leveraging clustering algorithms,our approach accurately categorizes diverse web applications,providing comprehensive and precise fingerprint *** experimental results,which are obtained on a dataset featuring various web application types,affirm the efficacy of the method,demonstrating its ability to achieve high accuracy and broad *** novel approach not only distinguishes between different web application types effectively but also demonstrates superiority in terms of classification accuracy and coverage,offering a robust solution to the challenges of web application fingerprint recognition.

关键词： Web application fingerprint recognition unsupervised learning clustering algorithm feature extraction automated testing network security

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BArcherFuzzer:An Android System Services Fuzzier via Transaction Dependencies of BpBinder

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Intelligent Automation & Soft Computing 2024年第3期39卷 527-544页

作者： Jiawei Qin Hua Zhang Hanbing Yan Tian Zhu Song Hu Dingyu Yan The State Key Laboratory of networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100080China The National computer network emergency response technical team/coordination center of china Beijing100012China

By the analysis of vulnerabilities of Android native system services,we find that some vulnerabilities are caused by inconsistent data transmission and inconsistent data processing logic between client and *** existing research cannot find the above two types of vulnerabilities and the test cases of them face the problem of low *** this paper,we propose an extraction method of test cases based on the native system services of the client and design a case construction method that supports multi-parameter mutation based on genetic algorithm and priority *** on the above method,we implement a detection tool-BArcherFuzzer to detect vulnerabilities of Android native system *** experiment results show that BArcherFuzzer found four vulnerabilities of hundreds of exception messages,all of them were confirmed by Google and one was assigned a Common Vulnerabilities and Exposures(CVE)number(CVE-2020-0363).

关键词： Android OS vulnerability detection binder fuzz testing genetic algorithm

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Automatic Malware Classification via PRICoLBP

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Chinese Journal of Electronics 2018年第4期27卷 852-859页

作者： YAN Hanbing ZHOU Hao ZHANG Honggang National computer network emergency response technical team/coordination center of china Beijing University of Posts and Telecommunications

Creating effective features is a critical issue in malware analysis. It requires a proper tradeoff between discriminative power and invariance. Previous studies have shown that it is fairly effective to design features based on the binary code. However, the current existing binary-based features seldom take into consideration the problem of obfuscation, such as relocated sections, incomplete code and redundant operations. In this paper, we propose a novel Pairwise rotation invariant co-occurrence local binary pattern(PRICo LBP) feature, and further extend it to incorporate the Term frequency-inverse document frequency(TFIDF) transform. Different from other static analysis techniques, our method not only achieves better linear separability, but also appears to be more resilient to obfuscation. In addition, we evaluate PRICo LBPTFIDF comprehensively on three datasets from different perspectives, e.g., classification performance, classifier selection and performance against obfuscation. What’s more,we compare our PRICoLBP-TFIDF method with other techniques, and demonstrate that PRICo LBP-TFIDF is quite an efficient and effective tradeoff between discriminative power and invariance.

关键词： Malware classification Pairwise rotation invariant co-occurrence local binary pattern Term frequency-inverse document frequency Texture classification Resilience to obfuscation

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WAF-Based Chinese Character Recognition for Spam Image Filtering

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Chinese Journal of Electronics 2018年第5期27卷 1050-1055页

作者： LI Siyuan LI Ruiguang XU Yuan ZHOU Hao YAN Hanbing XU Bin ZHANG Honggang Beijing University of Posts and Telecommunication National computer network emergency response technical team coordination center of china

We address the problem of filtering image spam, a kind of rapidly spread spam in which the text is embedded into images to defeat text-based spam ***, we focus on image spam with Chinese text as "spam" which is a more challenging task. A popular way to detect image spam is by Optical character recognition(OCR) system, which detects and recognizes the embedded text, then followed by a text classifier that discriminate spam from ham. However, spammers start to obscure image text to prevent OCR system discovering the spam text. To compensate for the shortcomings of OCR system, a novel method which essentially is a keyword reconstruction algorithm based on Word activation force(WAF) model is proposed. It is effective on discovering keywords, hence is benefit for the later classification stage and notably improve the performance of image spam filtering. The experimental results on a personal data set of spam images(publicly available) validate the effectiveness of our approach that outperforms the original OCR system in practical usage with complex background in image spam.

关键词： Spam image Chinese character recognition Keyword reconstruction Word activation force

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Modeling and Analysis of the Decentralized Interactive Cyber Defense Approach

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china Communications 2022年第10期19卷 116-128页

作者： Ming Liu Ruiguang Li Weiling Chang Jieming Gu Shouying Bai Jia Cui Lu Ma National computer network emergency response technical team/coordination center of china Beijing 100029China

Powered by the Internet and the ever-increasing level of informatization, the cyberspace has become increasingly complex and its security situation has become increasingly grim, which requires new adaptive and collaborative defense technologies. In this paper, we introduced an extended interactive multi-agent decision model for decentralized cyber defense. Based on the significant advantages of the cooperative multi-agent decision-making, the decentralized interactive decision model DI-MDPs and the corresponding interaction and retrieval algorithms are proposed. Then, we analyzed the interactive decision by the calculation and update processes of three matrices, the stability and evolutionary equilibrium of the proposed model are also analyzed. Finally, we evaluated the performance of the proposed algorithms based on open data sets and standard test environments, the experimental results shown that the proposed work will be more applicable in cyber defense.

关键词： cyber defense multi-agent coordination evolutionary game heuristic decision algorithm

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A Taint Analysis Framework Applied to Android Applications in the Packed State

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china Communications 2023年第3期20卷 336-346页

作者： Shouying Bai Lu Ma Huan Ma Wei Liu National computer network emergency response technical team/coordination center of china Beijing 100029China

In recent years,Android applications have caused personal privacy leaks *** order to analyze the malicious behavior,taint analysis technology can be used to track the API call chain,build a control-flow graph of function,and determine whether there is a security ***,with the continuous escalation of offensive and defensive confrontation of source code,more and more applications use reinforcement technology to prevent security practitioners from performing reverse analysis,therefore it is impossible to analyze function-behavior from the source ***,we design a framework of taint analysis that applied to the Android applications,which automatically unpacks the Android APKs,restores the real source code of the App,performs taint analysis,and generates a control-flow graph of *** tests showed that the system can cope with the current mainstream reinforcement technology and restore the real Dex file ***,compared with the number of nodes before packing,the generated control-flow graph had an explosive increase,which effectively assisted manual analysis of App with the privacy leakage behaviors.

关键词： privacy disclosure unpacked technology taint analysis

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A negative selection algorithm based on hierarchical clustering of self set

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Science china(Information Sciences) 2013年第8期56卷 203-215页

作者： CHEN Wen LI Tao LIU XiaoJie ZHANG Bing College of computer Science Sichuan University National computer network emergency response technical team Coordination Center of China

Negative selection algorithm(NSA) is an important method of generating artificial immune ***,the traditional NSAs aim at eliminating the self-recognized invalid detectors,by matching candidate detectors with the whole self *** matching process results in extremely low generation efficiency and significantly limits the application of *** this paper,an improved NSA called CB-RNSA,which is based on the hierarchical clustering of self set,is *** CB-RNSA,the self data is first preprocessed by hierarchical clustering,and then replaced by the self cluster centers to match with candidate detectors in order to reduce the distance calculation *** the detector generation process,the candidate detectors are restricted to the lower coverage space to reduce the detector *** the paper,probabilistic analysis is performed on non-self coverage of ***,termination condition of the detector generation procedure in CB-RNSA is *** is more reasonable than that of traditional NSAs,which are based on predefined detector *** theoretical analysis shows the time complexity of CB-RNSA is irrelevant to the self set ***,the difficult problem,in which the detector training cost is exponentially related to the size of self set in traditional NSAs,is resolved,and the efficiency of the detector generation under a big self set is also *** experimental results show that:under the same data set and expected coverage,the detection rate of CB-RNSA is higher than that of the classic RNSA and V-detector algorithms by 12.3% and 7.4% ***,the false alarm rate is lower by 8.5% and 4.9% respectively,and the time cost of CB-RNSA is lower by 67.6% and 75.7% respectively.

关键词： artificial immune system negative selection algorithm detector cluster

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