IEEE Transactions on Network Science and Engineering最新文献

Instantiating a Diffusion Network Model to Support Wildfire Management 实例化支持野火管理的扩散网络模型

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-04-14 DOI: 10.1109/TNSE.2025.3559681

Marc Demange;Alessia Di Fonso;Gabriele Di Stefano;Pierpaolo Vittorini

{"title":"Instantiating a Diffusion Network Model to Support Wildfire Management","authors":"Marc Demange;Alessia Di Fonso;Gabriele Di Stefano;Pierpaolo Vittorini","doi":"10.1109/TNSE.2025.3559681","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3559681","url":null,"abstract":"Wildfires require effective responses considering multiple constraints and conflicting goals. We provide a methodology and a tool enabling stakeholders to compute risk maps and use them in practical and realistic scenarios. The territory is modeled as a network where nodes are land patches subject to fire and links model the probability of fire spread from one patch to another. We discuss a risk function and show how to compute it effectively. We show how to instantiate the model on a real landscape. The methodology describes how to compute each patch's borders and probabilities of ignition and how to estimate the probability of fire spreading from one patch to a neighboring one. We embed the methodology into an ad-hoc modular tool-chain using geographical data, a fire simulator and geospatial tools. As a proof-of-concept, the tool-chain is applied in three different experiments on a region of Corsica, France, aiming at simulating a realistic scenario and measuring the sensitivity of the methodology with increasing wind speed or variable wind directions. We finally introduce the web application that incorporates the tool-chain and enables users to manipulate the model intuitively through an interactive map, evaluate what-if scenarios, and simulate the effects of different fire preventive measures.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"3374-3388"},"PeriodicalIF":6.7,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

TEAM: Temporal Adversarial Examples Attack Model Against Network Intrusion Detection System Applied to RNN 团队：针对网络入侵检测系统的时间对抗实例攻击模型应用于RNN

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-04-11 DOI: 10.1109/TNSE.2025.3560027

Ziyi Liu;Dengpan Ye;Long Tang;Yunming Zhang;Jiacheng Deng;Wanrong Kuang

{"title":"TEAM: Temporal Adversarial Examples Attack Model Against Network Intrusion Detection System Applied to RNN","authors":"Ziyi Liu;Dengpan Ye;Long Tang;Yunming Zhang;Jiacheng Deng;Wanrong Kuang","doi":"10.1109/TNSE.2025.3560027","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3560027","url":null,"abstract":"With the development of artificial intelligence, neural networks play a key role in network intrusion detection systems (NIDS). Despite the tremendous advantages, neural networks are susceptible to adversarial attacks. To improve the reliability of NIDS, many research has been conducted and plenty of solutions have been proposed. However, the existing solutions rarely consider the adversarial attacks against recurrent neural networks (RNN) with time steps, which would greatly affect the application of NIDS in real world. Therefore, we first propose a novel RNN adversarial attack model based on feature reconstruction called <bold>Temporal adversarial <bold>Examples <bold>Attack <bold>Model <bold>(TEAM), which applied to time series data and reveals the potential connection between adversarial and time steps in RNN. That is, the past adversarial examples within the same time steps can trigger further attacks on current or future original examples. Moreover, TEAM leverages Time Dilation (TD) to effectively mitigates the effect of temporal among adversarial examples within the same time steps. Experimental results show that in most attack categories, TEAM improves the misjudgment rate of NIDS on both black and white boxes, making the misjudgment rate reach more than 97.65%. Meanwhile, the maximum increase in the misjudgment rate of the NIDS for subsequent original examples exceeds 95.57%.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"3400-3415"},"PeriodicalIF":6.7,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

f-AnoGAN for Unsupervised Attack Detection in SDN Environment SDN环境下无监督攻击检测的anogan

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-04-10 DOI: 10.1109/TNSE.2025.3558936

Vitor Gabriel da Silva Ruffo;Luiz Fernando Carvalho;Jaime Lloret;Mario Lemes Proença Jr

{"title":"f-AnoGAN for Unsupervised Attack Detection in SDN Environment","authors":"Vitor Gabriel da Silva Ruffo;Luiz Fernando Carvalho;Jaime Lloret;Mario Lemes Proença Jr","doi":"10.1109/TNSE.2025.3558936","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3558936","url":null,"abstract":"Network management solutions remain essential for proper network service delivery. The software-defined networking (SDN) paradigm brought flexibility and programmability to today's large-scale networks, easing their governance. Another critical factor in the quality of network services is network security for protection against cyberattacks. This work proposes an unsupervised volume anomaly detection and mitigation system for securing SDN environments. We implement a fast AnoGAN (f-AnoGAN) to model legitimate user behavior and identify outlier samples. The generative network is trained on a low-dimensional representation of network traffic to reduce computational overhead. The f-AnoGAN model performance is further investigated through hyperparameter tuning and ablation study. The security system is evaluated on four public datasets: Orion, CIC-DDoS2019, CIC-IDS2017, and TON_IoT. We implement state-of-the-art alternative models for comparison analysis, namely Autoencoder, BiGAN, and FID-GAN. The f-AnoGAN presents improved class separation capacity and anomaly identification performance compared to the other models. The anomaly mitigation module can drop between 95% and 99% of malign traffic, supporting network resilience and correct functioning.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"3271-3285"},"PeriodicalIF":6.7,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Event-Triggered Zero-Gradient-Sum Distributed Constrained Optimization Over Jointly Connected Balanced Digraphs 联合连接平衡有向图上事件触发的零梯度和分布约束优化

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-04-10 DOI: 10.1109/TNSE.2025.3559905

Xinli Shi;Ying Wan;Guanghui Wen;Xinghuo Yu

{"title":"Event-Triggered Zero-Gradient-Sum Distributed Constrained Optimization Over Jointly Connected Balanced Digraphs","authors":"Xinli Shi;Ying Wan;Guanghui Wen;Xinghuo Yu","doi":"10.1109/TNSE.2025.3559905","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3559905","url":null,"abstract":"In the realm of distributed optimization (DO), it is expected to design a distributed algorithm that has a lower communication burden while handling general constraints over switching graphs. One promising approach is the zero-gradient-sum (ZGS) algorithm. However, existing ZGS-based discrete-time algorithms are limited to unconstrained DO on fixed network structures. This paper addresses this gap by first providing an event-triggered ZGS (ET-ZGS) algorithm for solving equality-constrained DO over uniformly jointly strongly connected (UJSC) and balanced digraphs. Sufficient conditions on the fixed step size are derived to guarantee the convergence for switching graphs. Specifically, when applied to fixed connected graphs, the proposed algorithm achieves linear convergence in solving equality-constrained DO with typical ET strategies; for UJSC graphs, it enables linear convergence in solving unconstrained DO. To further address inequality constraints, a distributed path-following ET-ZGS algorithm embedded with a finite-time max-consensus protocol is provided over UJSC digraphs, leveraging the barrier method akin to the interior-point method. Finally, two numerical examples are performed to verify the efficiency of the proposed algorithms.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"3389-3399"},"PeriodicalIF":6.7,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PPHMA: Privacy-Preserving Hybrid Multi-Task Allocation for Mobile Crowd Sensing 移动人群感知的隐私保护混合多任务分配

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-04-09 DOI: 10.1109/TNSE.2025.3559563

Xian Zhang;Xiaolin Qin;Haiwen Xu;Lin Li

{"title":"PPHMA: Privacy-Preserving Hybrid Multi-Task Allocation for Mobile Crowd Sensing","authors":"Xian Zhang;Xiaolin Qin;Haiwen Xu;Lin Li","doi":"10.1109/TNSE.2025.3559563","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3559563","url":null,"abstract":"With the widespread adoption of mobile smart devices, mobile crowd sensing(MCS) has provided better services for people. To meet the growing sensing demands within a limited budget, platforms have integrated two modes—opportunistic sensing and participatory sensing—to utilize their complementary strengths. However, location privacy issues may reduce workers' willingness to participate, thereby affecting task completion rates. Although existing methods have addressed privacy protection in a single sensing mode, there remains little focus on location privacy in hybrid sensing modes. There are two main limitations in privacy issues related to task allocation: (i) how to effectively preserve workers' location privacy in hybrid sensing modes, and (ii) the usual reliance on trusted third-party institution. To address these issues, we propose a privacy-preserving hybrid multi-task allocation for MCS (PPHMA). This approach preserves workers' location privacy without relying on a fully trusted third-party institution, while maximizing the number of tasks completed. Specifically, for opportunistic task allocation, we employ zero-knowledge range proofs to protect workers' location, thereby avoiding location privacy leaks. Subsequently, based on the performance capability indicator of opportunistic workers, we select appropriate workers for task allocation. For participatory task allocation, we employ a worker location obfuscation generation algorithm to locally generate and upload obfuscated locations, ensuring that both the worker's real and obfuscated locations satisfy <inline-formula><tex-math>$varepsilon$</tex-math></inline-formula>-Geo-Indistinguishability within the protected range. Then, based on the execution capability indicator of the participatory workers, we screen for candidate workers and use a greedy immune clone algorithm to optimize the workers' travel distances. Finally, we verify the effectiveness of the scheme through experiments using two real-world datasets.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"3360-3373"},"PeriodicalIF":6.7,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cost-Optimized Crowdsourcing for NLP via Worker Selection and Data Augmentation 通过工人选择和数据增强的成本优化的NLP众包

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-04-09 DOI: 10.1109/TNSE.2025.3559342

Liner Yang;Yujie Wang;Zhixuan Fang;Yaping Huang;Erhong Yang

{"title":"Cost-Optimized Crowdsourcing for NLP via Worker Selection and Data Augmentation","authors":"Liner Yang;Yujie Wang;Zhixuan Fang;Yaping Huang;Erhong Yang","doi":"10.1109/TNSE.2025.3559342","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3559342","url":null,"abstract":"This paper presents worker selection and data augmentation algorithms aimed at improving annotation quality and reducing costs in crowdsourcing for Natural Language Processing (NLP). Unlike previous studies targeting simpler tasks like binary classification, which require less contextual understanding, this study aims to provide a unified paradigm for a wider spectrum of NLP tasks, with sequence labeling and text generation as application showcases. Utilizing a Combinatorial Multi-Armed Bandit (CMAB) approach and a cost-effective human feedback mechanism, the proposed worker selection algorithm effectively addresses the challenge of label inter-dependency in NLP tasks. Additionally, our algorithm tackles the issues presented by imbalanced and small-scale datasets through data augmentation methods. Experiments on the CoNLL 2003 NER, Chinese OEI, and YACLC datasets demonstrated the algorithm's efficiency, achieving up to 100.04% of the expert-only baseline <inline-formula><tex-math>${text{F}}$</tex-math></inline-formula>-score and 65.97% cost savings. A dataset-independent experiment yielded 97.56% of the expert baseline <inline-formula><tex-math>${text{F}}$</tex-math></inline-formula>-score and 59.88% cost savings. We also provide a theoretical analysis proving our worker selection framework achieves sub-linear regret.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"3343-3359"},"PeriodicalIF":6.7,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distributed Minmax Strategy for Multi-Agent Systems With Multiple Disturbances in Graphical Games 图形游戏中多干扰多智能体系统的分布式最小极大策略

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-04-09 DOI: 10.1109/TNSE.2025.3559028

Chunping Xiong;Qian Ma

引用次数: 0

Distributed Adaptive NN Resilient Optimal Control for Heterogeneous Vehicular Platoon Systems Under DoS Attacks DoS攻击下异构车辆排系统的分布式自适应神经网络弹性最优控制

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-04-09 DOI: 10.1109/TNSE.2025.3559130

Zixin Tian;Yongming Li;Shaocheng Tong

引用次数: 0

Graph Attentional Based Agglomerative Cluster for UAV Swarm Networks 基于图关注的无人机群网络聚类

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-04-09 DOI: 10.1109/TNSE.2025.3559215

Shan Huang;Haipeng Yao;Xiaoman Wang;Tianle Mai;Zunliang Wang;Song Guo

{"title":"Graph Attentional Based Agglomerative Cluster for UAV Swarm Networks","authors":"Shan Huang;Haipeng Yao;Xiaoman Wang;Tianle Mai;Zunliang Wang;Song Guo","doi":"10.1109/TNSE.2025.3559215","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3559215","url":null,"abstract":"In recent years, UAVs have been widely employed in the construction of post-disaster emergency communication networks due to their flexible mobility and self-organizing capabilities, enabling them to quickly and spontaneously establish communication links. Post-disaster rescue efforts, restoring connectivity and communication, as well as providing disaster information, all require strong support from network applications. However, an essential element in the development of effective UAV swarm-based applications is the network system. Compared to the fixed networks, UAV swarm networks present unique challenges in design and implementation due to its characteristics of high mobility nodes, unstable links, and dynamic topology. Recently, clustering technology has gained recognition as an effective approach to constructing stable UAV swarm networks. In this paper, for UAV swarm networks, we propose a graph attention-based agglomerative clustering algorithm. This algorithm allows UAV nodes to learn similarity relationships through a graph attention network. By considering the mobility similarity between UAV nodes, each UAV node can merge with its adjacent nodes. Furthermore, we also design a cluster head selection algorithm based on mixed strategy games. The algorithm's effectiveness and accuracy were demonstrated by simulation results, which showed a 80.04% increase in network lifetime compared to baseline algorithms.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"3311-3327"},"PeriodicalIF":6.7,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mobility-Aware Mode Selection, Relay Selection, and Resource Allocation for D2D Communication D2D通信的移动感知模式选择、中继选择和资源分配

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-04-09 DOI: 10.1109/TNSE.2025.3559236

Toha Ardi Nugraha;Pavel Mach;Zdenek Becvar

{"title":"Mobility-Aware Mode Selection, Relay Selection, and Resource Allocation for D2D Communication","authors":"Toha Ardi Nugraha;Pavel Mach;Zdenek Becvar","doi":"10.1109/TNSE.2025.3559236","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3559236","url":null,"abstract":"Mobility management and radio resource management are critical aspects of device-to-device (D2D) communication due to the coexistence of cellular user equipments (CUEs) and D2D user equipments (DUEs) operating within the same spectrum. Therefore, in this paper, we target a problem of D2D communication for mobile users and we address it via joint selection of communication mode (i.e., cellular mode, relay mode, D2D mode), selection of relay, and allocation of resources to maximize the sum rate of D2D pairs while ensuring quality of service for all CUEs. As the formulated problem is a binary integer nonlinear programming problem, which is of very high complexity, we first develop a preliminary greedy approach virtually pre-selecting only mode and relay for each D2D pair. Then, we enhance the preliminary approach towards a comprehensive greedy algorithm for joint mode selection, relay selection, and resource allocation. We also address implementation aspects, including complexity, channel quality acquisition, and signaling message exchange for the management of the proposed solution for mobile users. The simulations demonstrate that our proposed scheme increases the sum rate of D2D pairs by approximately 20% if compared to the best performing related work.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"3328-3342"},"PeriodicalIF":6.7,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0