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Granular classifier:Building traffic granules for encrypted traffic classification based on granular computing

Digital Communications and networks 2024年第5期10卷 1428-1438页

作者： Xuyang Jing Jingjing Zhao Zheng Yan Witold Pedrycz Xian Li State Key Laboratory on Integrated Services Networks School of Cyber EngineeringXidian UniversityChina Department of Electrical and Computer Engineering University of AlbertaCanada Institute for Future(IFF) Qingdao UniversityQingdaoChina

Accurate classification of encrypted traffic plays an important role in network ***,current methods confronts several problems:inability to characterize traffic that exhibits great dispersion,inability to classify traffic with multi-level features,and degradation due to limited training traffic *** address these problems,this paper proposes a traffic granularity-based cryptographic traffic classification method,called Granular Classifier(GC).In this paper,a novel Cardinality-based Constrained Fuzzy C-Means(CCFCM)clustering algorithm is proposed to address the problem caused by limited training traffic,considering the ratio of cardinality that must be linked between flows to achieve good traffic ***,an original representation format of traffic is presented based on granular computing,named Traffic Granules(TG),to accurately describe traffic structure by catching the dispersion of different traffic *** granule is a compact set of similar data with a refined boundary by excluding *** on TG,GC is constructed to perform traffic classification based on multi-level *** performance of the GC is evaluated based on real-world encrypted network traffic *** results show that the GC achieves outstanding performance for encrypted traffic classification with limited size of training traffic and keeps accurate classification in dynamic network conditions.

关键词： Encrypted traffic classification Semi-supervised clustering Granular computing Anomaly detection

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The governance technology for blockchain systems:a survey

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Frontiers of computer Science 2024年第2期18卷 181-197页

作者： Guocheng ZHU Debiao HE Haoyang AN Min LUO Cong PENG School of Cyber Science and Engineering Wuhan UniversityWuhan 430072China Shandong Provincial Key Laboratory of Computer Networks Qilu University of Technology(Shandong Academy of Sciences)Jinan 250014China

After the Ethereum DAO attack in 2016,which resulted in significant economic losses,blockchain governance has become a prominent research ***,there is a lack of comprehensive and systematic literature review on blockchain *** deeply understand the process of blockchain governance and provide guidance for the future design of the blockchain governance model,we provide an in-depth review of blockchain *** this paper,first we introduce the consensus algorithms currently used in blockchain and relate them to governance ***,we present the main content of off-chain governance and investigate two well-known off-chain governance ***,we investigate four common on-chain governance voting techniques,then summarize the seven attributes that the on-chain governance voting process should meet,and finally analyze four well-known on-chain governance blockchain projects based on the previous *** hope this survey will provide an in-depth insight into the potential development direction of blockchain governance and device future research agenda.

关键词： blockchain governance off-chain governance on-chain governance voting

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Achieving Physical Layer Security Against Location Unknown Eavesdroppers via Friendly Jammer

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IEEE/CAA Journal of Automatica Sinica 2023年第10期10卷 2038-2040页

作者： Heng Zhang Jianwei Sun Xin Wang Chenglong Gong School of Computer Engineering Jiangsu Ocean UniversityLianyungang 222000China School of Electronic Engineering Jiangsu Ocean UniversityLianyungang 222000China Shandong Provincial Key Laboratory of Computer Networks Shandong Computer Science CenterQilu University of TechnologyJinan 250014China

Dear Editor, This letter is concerning friendly jamming unmanned aerial vehicles(UAVs) to assist in the safe communication of UAV base stations. Due to the openness of UAV wireless communication, it is vulnerable to attacks leading to information disclosure or blockage. To address this issue, friendly jamming UAVs can assist UAV base stations and improve the security of wireless communications.

关键词： communication letter base

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T³Planner: Multi-Phase Planning Across Structure-Constrained Optical, IP, and Routing Topologies

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IEEE Journal on Selected Areas in Communications 2025年第5期43卷 1823-1839页

作者： Hao, Yijun Yang, Shusen Li, Fang Zhang, Yifan Zhao, Cong Ren, Xuebin Zhao, Peng Xu, Chenren Wang, Shibo Xi’an Jiaotong University National Engineering Laboratory for Big Data Analytics Xi’an710049 China Xi’an Jiaotong University National Engineering Laboratory for Big Data Analytics Ministry of Education Key Laboratory for Intelligent Networks and Network Security Xi’an710049 China Peking University School of Computer Science Beijing100871 China The Chinese University of Hong Kong Department of Computer Science and Engineering Hong Kong National Engineering Laboratory for Big Data Analytics Xi'an Jiaotong University Xi'an710049 China

Network topology planning is an essential multi-phase process to build and jointly optimize the multi-layer network topologies in wide-area networks (WANs). Most existing practices target single-phase/layer planning, and are incapable of satisfying all rigorous topological structure constraints (e.g., dual-homing rings) defined by network standards and operators, especially in large-scale networks. These significantly limit their usability and performance in production networks. We consider a general topology planning problem with typical structure constraints over three essential phases (greenfield, reconfiguration, and site expansion) and topological layers (optical, IP, and routing topologies). We present, T3Planner, a novel practical solver to this problem in production. Specifically, we develop a structure-driven encoder based on graph neural network (GNN) for concise structure encoding, and design a new learning framework with optical-centric layer compression/reconstruction and rule-aided reinforcement learning (RL) for fast convergence and high performance. Extensive experiments on nine real topologies demonstrate that T3Planner scales to large optical networks with hundreds of sites, saves 46.6% cost, and supports 3.12x more demand when compared to related existing approaches. © 1983-2012 IEEE.

关键词： Network topology

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Leveraging UAV-RIS Reflects to Improve the Security Performance of Wireless Network Systems

IEEE Networking Letters

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IEEE Networking Letters 2023年第2期5卷 81-85页

作者： Sun, Jianwei Zhang, Heng Wang, Xin Yang, Ming Zhang, Jian Li, Hongran Gong, Chenglong Jiangsu Ocean University School of Electronic Engineering Lianyungang222000 China Jiangsu Ocean University School of Computer Engineering Lianyungang222000 China Shandong Provincial Key Laboratory of Computer Networks Shandong Computer Science Center Jinan250014 China

In this letter, a novel application method of reconfigurable intelligent surfaces (RIS) is proposed, which installs a RIS on an unmanned aerial vehicle (UAV) rather than fixed to buildings. When the location information of the eavesdropper is unknown, the UAV's rapid deployment and RIS's ability to change the transmission channel are utilized to dynamically optimize the UAV's flight trajectory and RIS's phase shift. The trajectory of the UAV and phase shift of the RIS are optimized to avoid the risk of potential eavesdropping and improve the average downlink secrecy rate of the system. This letter utilizes Q-learning and Deep Q-network (DQN) algorithms to solve the problem. Experiments show that RIS can reduce the flight distance of the UAV on the premise of ensuring security. The scenarios where the two algorithms are applicable are analyzed, and the DQN algorithm is more suitable for the scenarios of large state and action spaces. Also, the experimental results imply that the RIS-assisted UAV improves the average downlink secrecy rate and system security. © 2019 IEEE.

关键词： Signal to noise ratio

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Comments on 'VERSA: Verifiable Secure Aggregation for Cross-Device Federated Learning'

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IEEE Transactions on Dependable and Secure Computing 2024年第1期21卷 499-500页

作者： Luo, Fucai Wang, Haiyan Yan, Xingfu Zhejiang Gongshang University College of Computer and Information Engineering Hangzhou310000 China Peng Cheng Laboratory Department of New Networks Shenzhen518066 China South China Normal University School of Computer Science Guangzhou510631 China

Federated learning (FL) allows a large number of users to collaboratively train machine learning (ML) models by sending only their local gradients to a central server for aggregation in each training iteration, without sending their raw training data. The main security issues of FL, that is, the privacy of the gradient vector and the correctness verification of the aggregated gradient, are gaining increasing attention from industry and academia. To protect the privacy of the gradient, a secure aggregation was proposed;to verify the correctness of the aggregated gradient, a verifiable secure aggregation that requires the server to provide a verifiable aggregated gradient was proposed. In 2021, Hahn et al. proposed VERSA, a verifiable secure aggregation. However, in this article, we will point out a flaw in VERSA, which indicates that VERSA does not work. To address the flaw, we present several approaches with different advantages and disadvantages. We hope that by identifying the flaw, similar errors can be avoided in future designs of verifiable secure aggregation. © 2004-2012 IEEE.

关键词： Learning systems

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Analog parallel processor for broadband multifunctional integrated system based on silicon photonic platform

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Light(Science & Applications) 2025年第3期14卷 746-756页

作者： Na Qian Defu Zhou Haowen Shu Ming Zhang Xingjun Wang Daoxin Dai Xiao Deng Weiwen Zou State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center(imLic)Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghaiChina State Key Laboratory of Advanced Optical Communications System and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBejingChina State Key Laboratory of Extreme Photonics and Instrumentation College of Optical Science and EngineeringInternational Research Center for Advanced PhotonicsZhejiang UniversityHangzhouChina

Sharing the hardware platform between diverse information systems to establish full cooperation among different functionalities has attracted substantial ***,broadband multifunctional integrated systems with large operating frequency ranges are challenging due to the bandwidth and computing speed restrictions of electronic ***,we report an analog parallel processor(APP)based on the silicon photonic platform that directly discretizes and parallelizes the broadband signal in the analog *** APP first discretizes the signal with the optical frequency comb and then adopts optical dynamic phase interference to reassign the analog signal into 2N parallel *** photonic analog parallelism,data rate and data volume in each sequence are simultaneously compressed,which mitigates the requirement on each parallel computing ***,the fusion of the outputs from each computing core is equivalent to directly processing broadband *** the proof-of-concept experiment,two-channel analog parallel processing of broadband radar signals and high-speed communication signals is implemented on the single photonic integrated *** bandwidth of broadband radar signal is 6 GHz and the range resolution of 2.69 cm is *** wireless communication rate of 8 Gbit/s is also *** the bandwidth and speed limitations of the single-computing core along with further exploring the multichannel potential of this architecture,we anticipate that the proposed APP will accelerate the development of powerful optoelectronic processors as critical support for applications such as satellite networks and intelligent driving.

关键词： analog parallel processor sharing hardware platform multifunctional integrated systems establish full cooperation different functionalities analog parallel processor app based silicon photonic platform electronic circuitryherewe broadband signal

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Optimizing Polynomial-Time Solutions to a Network Weighted Vertex Cover Game

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 512-523页

作者： Jie Chen Kaiyi Luo Changbing Tang Zhao Zhang Xiang Li the Adaptive Networks and Control Laboratory Department of Electronic EngineeringFudan UniversityShanghai 200433China the College of Mathematics and Computer Science Zhejiang Normal UniversityJinhua 321004 Yuxi Middle School Taizhou 317399China IEEE the College of Physics and Electronics Information Engineering Zhejiang Normal UniversityJinhua 321004China the College of Mathematics and Computer Science Zhejiang Normal UniversityJinhua 321004China the Adaptive Networks and Control Laboratory Department of Electronic EngineeringFudan UniversityShanghai 200433 the Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous SystemsTongji UniversityShanghai 201210China

Weighted vertex cover(WVC)is one of the most important combinatorial optimization *** this paper,we provide a new game optimization to achieve efficiency and time of solutions for the WVC problem of weighted *** first model the WVC problem as a general game on weighted *** the framework of a game,we newly define several cover states to describe the WVC ***,we reveal the relationship among these cover states of the weighted network and the strict Nash equilibriums(SNEs)of the ***,we propose a game-based asynchronous algorithm(GAA),which can theoretically guarantee that all cover states of vertices converging in an SNE with polynomial ***,we improve the GAA by adding 2-hop and 3-hop adjustment mechanisms,termed the improved game-based asynchronous algorithm(IGAA),in which we prove that it can obtain a better solution to the WVC problem than using a the ***,numerical simulations demonstrate that the proposed IGAA can obtain a better approximate solution in promising computation time compared with the existing representative algorithms.

关键词： Game-based asynchronous algorithm(GAA) game optimization polynomial time strict Nash equilibrium(SNE) weighted vertex cover(WVC)

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The Task Collaborative Migration Method for Marine IoT Based on Edge Computing-RESTful Architecture 6

The Task Collaborative Migration Method for Marine IoT Based...

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6th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2024

作者： Hu, Yifan Wang, Fuqiang School of Information and Control Engineering Qingdao University of Technology Qingdao China Shandong Computer Science Center and Shandong Provincial Key Laboratory of Computer Networks Jinan China

ISBN: (纸本)9798350344349

Marine Internet of Things (Marine IoT) has garnered increasing interest in monitoring oceanic environments. But establishing a Marine IoT system for observing and processing marine environmental data presents various challenges. These include limited underwater communication bandwidth, and uneven distribution of tasks among data-sensing devices. This paper proposes an Edge Computing-RESTful (ECR) architecture to efficiently integrate and process the substantial volume of data gathered through marine observations. 1) The ECR method is introduced for task collaborative migration, aiming to schedule and manage the tasks within the Marine IoT system. 2) Through unified scheduling and management of tasks, the edge gateway can facilitate migration, scheduling, and interaction of task loads among various edge sensing devices. The proposed dynamic and adaptive approach matches computing tasks with edge sensing devices, minimizing energy consumption and migration delay within the Marine IoT system. Simulation results validate the superiority of the proposed method for Marine IoT, showcasing improved performance metrics such as reduced time delays and lower energy consumption during task collaborative migration. © 2024 IEEE.

关键词： Edge computing

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Incremental Semi-Supervised Learning for Data Streams Classification in Internet of Things

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IEEE Transactions on Network and Service Management 2025年第3期22卷 2489-2501页

作者： Jiang, Jun Wang, Bin Tang, Quan Zhong, Guoxiang Tang, Xuhao Rodrigues, Joel J. P. C. Pengcheng Laboratory Department of New Networks Shenzhen China South China University of Technology School of Computer Science and Engineering Guangzhou510006 China Lusófona University COPELABS Campo Grande 376 Lisbon1749-024 Portugal

Data stream classification is widely used in Internet of Things (IoT) scenarios such as health monitoring, anomaly detection and online diagnosis. Due to the continuous data stream changing dynamically over time, it is impossible to classify all the data simultaneously. Moreover, labeling each sample in practical data stream applications is time-and resource-consuming. The realistic situation is that only a few instances in a data stream are labeled. Therefore, classifying data streams with limited labels has become challenging in IoT scenarios. In this paper, we propose an incremental dynamic weighted semi-supervised method for classifying IoT data streams. Considering the dynamics and continuity in data streams, we use a chunk-based approach to learn the features in the data stream and assign weights to the classifier dynamically. Moreover, we deploy incremental learning methods to continuously learn from the sampled labeled data stream to update the classifier model, which can take advantage of newly incoming labeled data to improve learning performance. Experimental evaluations on seven IoT datasets show that the proposed method outperforms semi-supervised methods in accuracy, precision, and geometric mean (Gmean) by 10% and 5% over supervised methods, respectively. © 2004-2012 IEEE.

关键词： Self-supervised learning

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