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Journal of network Intelligence 2025年第1期10卷 541-558页

作者： Xu, Peiming Jiang, Yixin Kuang, Xiaoyun Luo, Yu Chen, Jiahui Guangdong Provincial Key Laboratory of Power System Network Security CSG Guangzhou510000 China School of Computer Science and Technology Guangdong University of Technology Guangzhou510006 China

High utility itemset mining is a research topic of the pattern mining domain, which has been widely applied in reality during the past decade. Although most high utility itemset mining algorithms show significant execution performance regarding runtime and memory usage, numerous results are useless for users. Targeted high utility itemset mining can reduce the number of high utility itemsets and improve the efficiency of pattern analysis. However, the targeted high utility itemset mining task aims to find targeted high utility itemsets with as many items as possible. Users are not that interested in long results in actual scenarios. Therefore, in this article, we first formulate the problem and then address this issue by proposing a new algorithm named THL for mining targeted high utility itemset within length constraints, based on utility list structure. Furthermore, to improve the performance of the novel algorithm, THL adopts several efficiency pruning strategies, including length and utility aspects. Finally, we conduct an extensive experimental evaluation to compare the SOTA algorithms with THL on several datasets. © 2025, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： data mining high utility itemset length constraint targeted items

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The Study of Multi-type computing Power Trading Mechanism in computing Power network Based on Blockchain and Combinatorial Double Auction 24

The Study of Multi-type Computing Power Trading Mechanism in...

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4th International Conference on Artificial Intelligence, Big Data and Algorithms, CAIBDA 2024

作者： Zhao, Yue Wang, Jizhi Kong, Lingrui Sui, Tongtong Shandong Computer Science Center National Supercomputer Center in Jinan Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Provincial Key Laboratory of Industrial Network and Information System Security Qilu University of Technology Shandong Academy of Sciences Jinan Shandong China Quancheng Laboratory Jinan Key Laboratory of Digital Security Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Qilu University of Technology Shandong Academy of Sciences Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan Shandong China

ISBN: (纸本)9798400710247

The advancement of 5G and mobile internet technologies has propelled the development of emerging businesses and applications, demanding higher requirements for network bandwidth and computational resources. To address this challenge, the computing power network (CPN) has emerged. The CPN integrates computing and networking in depth, achieving collaborative allocation of distributed computing resources, enhancing the efficient utilization of computing resources, and improving user experiences in network services. However, in the development of fields such as Extended Reality (XR), Smart Healthcare, Connected Vehicles, and Artificial Intelligence (AI), there is a multidimensional, complex, and rapidly growing demand for computing resources. Therefore, it is crucial to establish a trading mechanism that integrates multiple computing resources in CPN. In this paper, a computing power trading scheme based on blockchain and combinatorial double auction is proposed. Firstly, a computing power trading system based on blockchain was designed, leveraging the decentralized and highly secure characteristics of blockchain technology to enhance the security of computing power transactions. Furthermore, a multi-type computing power trading mechanism (MCPT) based on blockchain and combinatorial double auction was introduced. The use of combinatorial double auctions as an incentive mechanism enables the trading of multiple computing power resources and results in high social welfare. Moreover, a discrete rime optimization algorithm (DRIME) is designed in the proposed mechanism (MCPT) to better solve the computing trading problem. Through simulation experiments, the effectiveness of the approach is validated. © 2024 Copyright held by the owner/author(s).

关键词： computing power

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Structure-based Street Tree Extraction from Mobile Laser Scanning Point Clouds 2022

Structure-based Street Tree Extraction from Mobile Laser Sca...

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5th International Conference on Image and Graphics Processing, ICIGP 2022

作者： Hao, Wen Zuo, Zhanbin Liang, Wei School of Computer Science and Engineering Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an University of Technology China Shaanxi Key Laboratory for Network Computing and Security Technology China

ISBN: (纸本)9781450395465

We present an automatic method based on structure analysis for extracting street trees from mobile laser scanning (MLS) data. Tree trunk and canopy can be characterized by the shape information and height above the ground level. Therefore, MLS point clouds are firstly divided into three layers (ground, low layer above the ground, high layer above the ground) with respect to the vertical height. For the points above the ground, the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering method is applied to cluster the points into segments and geometrical features are used to extract trunk candidates and canopy candidates. Then, a "structure-matching" strategy is proposed based on minimum bounding rectangle (MBR) mapping to extract the tree candidates. Finally, a slicing method based on axial symmetry is proposed to segment the overlapped canopy. The experimental results show that the proposed method can quickly extract individual trees from massive street point clouds. © 2022 ACM.

关键词： Extraction

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Achieving dynamic privacy measurement and protection based on reinforcement learning for mobile edge crowdsensing of IoT

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Digital Communications and networks 2024年第2期10卷 380-388页

作者： Renwan Bi Mingfeng Zhao Zuobin Ying Youliang Tian Jinbo Xiong Fujian Provincial Key Laboratory of Network Security and Cryptology College of Computer and Cyber SecurityFujian Normal UniversityFuzhou350117China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic TechnologyGuilin541004China Faculty of Data Science City University of Macao999078MacaoChina State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China

With the maturity and development of 5G field,Mobile Edge CrowdSensing(MECS),as an intelligent data collection paradigm,provides a broad prospect for various applications in ***,sensing users as data uploaders lack a balance between data benefits and privacy threats,leading to conservative data uploads and low revenue or excessive uploads and privacy *** solve this problem,a Dynamic Privacy Measurement and Protection(DPMP)framework is proposed based on differential privacy and reinforcement ***,a DPM model is designed to quantify the amount of data privacy,and a calculation method for personalized privacy threshold of different users is also ***,a Dynamic Private sensing data Selection(DPS)algorithm is proposed to help sensing users maximize data benefits within their privacy ***,theoretical analysis and ample experiment results show that DPMP framework is effective and efficient to achieve a balance between data benefits and sensing user privacy protection,in particular,the proposed DPMP framework has 63%and 23%higher training efficiency and data benefits,respectively,compared to the Monte Carlo algorithm.

关键词： Mobile edge crowdsensing Dynamic privacy measurement Personalized privacy threshold Privacy protection Reinforcement learning

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A Novel Construction of Updatable Identity-Based Hash Proof System and Its Applications

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Chinese Journal of Electronics 2023年第3期32卷 564-576页

作者： QIAO Zirui ZHOU Yanwei YANG Bo ZHANG Wenzheng ZHANG Mingwu School of Computer Science Shaanxi Normal University State Key Laboratory of Cryptology Science and Technology on Communication Security Laboratory Henan Key Laboratory of Network Cryptography Technology School of Computere Hubei University of Technology

In the previous works, to further provide the continuous leakage resilience for the identity-based encryption scheme, a new cryptography primitive, called updatable identity-based hash proof system(U-IB-HPS),was proposed. However, most of the existing constructions have some deficiencies, they either do not have perfect key update function or the corresponding security with tight reduction relies on a non-static complexity assumption. To address the above problems, a new construction of U-IB-HPS is created, and the corresponding security of our system is proved based on the static complexity assumption. Also, the corresponding comparisons and analysis of performances show that our proposal not only achieves the perfect key update function and the anonymity, but also has the tight security reduction. In additional, our proposal achieves the same computational efficiency as other previous systems. To further illustrate the practical function of U-IB-HPS, a generic method of non-interactive data authorization protocol with continuous leakage resilience is designed by employing U-IB-HPS as an underlying tool, which can provide continuous leakage-resilient data authorization function for the cloud computing. Hence, the application field of U-IB-HPS is further extended through our study.

关键词： Authorization Cloud computing Protocols Identity-based encryption Complexity theory Computational efficiency Proposals

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Malicious Client Detection with Differential Privacy Constraints Based on Model Update Slicing and K-Means Clustering 6

Malicious Client Detection with Differential Privacy Constra...

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6th International Conference on Frontier Technologies of Information and Computer, ICFTIC 2024

作者： Qi, Mengshi Wang, Xin He, Yunpeng Yang, Ming Wu, Xiaoming Key Laboratory of Computing Power Network and Information Security Jinan250014 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250014 China

ISBN: (纸本)9798331541750

Federated learning (FL) is a decentralized machine learning technique that protects data privacy by trainng models locally on devices and sharing only model updates instead of raw data. However, FL also faces multiple security challenges. Clientside poisoning attacks can compromise global model training by injecting malicious updates. Additionally, the server may infer private information from client model updates. Most existing studies address these two risks separately, lacking a systematic analysis and response to their combined threats. This paper proposes a method called Sliced-Clustering Guard (SCGuard), which slices gradients and performs clustering analysis on each segment, enabling the server to more accurately detect malicious updates and effectively differentiate malicious client updates with differential privacy (DP) protection. Experimental results demonstrate that SCGuard can mitigate poisoning attacks while effectively safeguarding clients' sensitive information. © 2024 IEEE.

关键词： Federated learning

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On the complete weight distributions of quantum error-correcting codes

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Chinese Physics B 2023年第5期32卷 272-287页

作者：杜超马智熊茂胜 State Key Laboratory of Mathematical Engineering and Advanced Computing Zhenghzhou 450001China Henan Key Laboratory of Network Cryptography Technology Zhenghzhou 450001China Department of Mathematics Hong Kong University of Science and TechnologyHong KongChina

In a recent paper, Hu et al. defined the complete weight distributions of quantum codes and proved the Mac Williams identities, and as applications they showed how such weight distributions may be used to obtain the singleton-type and hamming-type bounds for asymmetric quantum codes. In this paper we extend their study much further and obtain several new results concerning the complete weight distributions of quantum codes and applications. In particular, we provide a new proof of the Mac Williams identities of the complete weight distributions of quantum codes. We obtain new information about the weight distributions of quantum MDS codes and the double weight distribution of asymmetric quantum MDS codes. We get new identities involving the complete weight distributions of two different quantum codes. We estimate the complete weight distributions of quantum codes under special conditions and show that quantum BCH codes by the Hermitian construction from primitive, narrow-sense BCH codes satisfy these conditions and hence these estimate applies.

关键词： quantum codes complete weight distributions Mac Williams identities BCH codes

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NDFuzz:a non-intrusive coverage-guided fuzzing framework for virtualized network devices

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Cybersecurity 2023年第1期6卷 54-74页

作者： Yu Zhang Nanyu Zhong Wei You Yanyan Zou Kunpeng Jian Jiahuan Xu Jian Sun Baoxu Liu Wei Huo Institute of Information Engineering Chinese Academy of SciencesBejingChina School of Cyber Security University of Chinese Academy of SciencesBejingChina Key Laboratory of Network Assessment Technology Chinese Academy of SciencesBeijingChina Beijing Key Laboratory of Network Security and Protection Technology BeijingChina Renmin University of China BeijingChina

network function virtualization provides programmable in-network middlewares by leveraging virtualization tech-nologies and commodity hardware and has gained popularity among all mainstream network device *** it is challenging to apply coverage-guided fuzzing,one of the state-of-the-art vulnerability discovery approaches,to those virtualized network devices,due to inevitable integrity protection adopted by those *** this paper,we propose a coverage-guided fuzzing framework NDFuzz for virtualized network devices with a novel integrity protec-tion bypassing method,which is able to distinguish processes of virtualized network devices from hypervisors with a carefully designed non-intrusive page global directory inference *** implement NDFuzz atop of two black-box fuzzers and evaluate NDFuzz with three representative network protocols,SNMP,DHCP and NTP,on nine popular virtualized network *** obtains an average 36%coverage improvement in comparison with its black-box *** discovers 2 O-Day vulnerabilities and 11-Day vulnerability with coverage guidance while the black-box fuzzer can find only one of *** discovered vulnerabilities are confirmed by corresponding vendors.

关键词： Coverage-guided fuzzing network devices network function virtualization

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Remote Data Auditing for Cloud-Assisted WBANs with Pay-as-You-Go Business Model

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Chinese Journal of Electronics 2023年第2期32卷 248-261页

作者： LI Yumei ZHANG Futai School of Computer Science Hubei University of Technology Fujian Provincial Key Laboratory of Network Security and Cryptology College of Computer and Cyber SecurityFujian Normal University

As an emerging technology, cloud-assisted wireless body area networks(WBANs) provide more convenient services to users. Recently, many remote data auditing protocols have been proposed to ensure the data integrity and authenticity when data owners outsourced their data to the cloud. However, most of them cannot check data integrity periodically according to the pay-as-you-go business model. These protocols also need high tag generation computation overhead, which brings a heavy burden for data owners. Therefore, we construct a lightweight remote data auditing protocol to overcome all above drawbacks. Our work can be deployed in the public environment without secret *** makes use of certificate-based cryptography which gets rid of certificate management problems, key escrow problems, and secret channels. The security analysis illustrates that the proposed protocol is secure. Moreover, the performance evaluation implies that our work is available in cutting down computation and communication overheads.

关键词： Wireless communication Performance evaluation Protocols Computational modeling Data integrity Data models Computational efficiency

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DDoS Attack Detection Based on Information Entropy Feature Extraction in Software Defined networks

DDoS Attack Detection Based on Information Entropy Feature E...

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2023 International Conference on networking and network Applications, NaNA 2023

作者： Ji, Wenjiang Yang, Yixin Zhang, Yaling Wang, Yichuan Tian, Mengjie Qiu, Yuan Xi'an University of Technology School of Computer Science and Engineering Xi'an China Shaanxi Key Laboratory for Network Computing and Security Technology China

ISBN: (纸本)9798350327380

Distributed Denial of Service(DDoS) attacks target the forwarding-control separation feature of Software-Defined networking(SDN) to launch attacks, causing network disruptions. Therefore security against DDoS attack detection for SDN controllers is the focus of current research. This paper proposes an Extreme Gradient Boosting (XGBoost) DDoS attack detection algorithm based on a combination of information gain and recursive feature elimination algorithms. We evaluated the performance of the method using the CICDDoS2019 dataset. This method works well in multi-classification model for attack detection with an accuracy of 93.41%. © 2023 IEEE.

关键词： Software defined networking

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