Computer Networks最新文献_第3页

Personalized task allocation based on graph neural networks in mobile crowd sensing 移动人群感知中基于图神经网络的个性化任务分配

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-15 DOI: 10.1016/j.comnet.2025.111675

Shuang Ding , Weijie Sun , Xin He , Anny Li

{"title":"Personalized task allocation based on graph neural networks in mobile crowd sensing","authors":"Shuang Ding , Weijie Sun , Xin He , Anny Li","doi":"10.1016/j.comnet.2025.111675","DOIUrl":"10.1016/j.comnet.2025.111675","url":null,"abstract":"<div><div>Personalized Task Allocation (PTA) has emerged as a pivotal challenge in mobile crowd sensing, aiming to balance platform costs and worker satisfaction through optimized task allocation, yet facing dual critical challenges: the exponential growth of problem scale driven by technological advancements and severe data sparsity caused by limited historical allocation and privacy constraints. To address these challenges, this paper proposes PTA-GNNTR, a novel two-stage graph neural network framework where Stage 1 develops a Graph Neural Network-based Task Recommendation (GNNTR) that integrates multi-dimensional factors (historical records, social relationships, and task attributes) using graph convolutional networks, attention mechanisms, and multi-layer perceptrons to enhance feature representations and generate satisfaction-oriented pre-allocation results, while Stage 2 constructs a worker-task allocation bipartite graph (WTABG) for globally optimal matching to minimize platform costs under multiple constraints. Experimental results demonstrate PTA-GNNTR’s superiority in large-scale sparse-data scenarios, revealing the importance hierarchy of allocation factors (historical records <span><math><mo>></mo></math></span> virtual <span><math><mo>></mo></math></span> physical social relationships) and outperforming baselines across worker satisfaction, completion rate, and execution cost metrics, ultimately presenting a paradigm-shifting methodology that fuses GNNs with bipartite graph optimization to deliver a scalable solution for next-generation crowd sensing systems.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111675"},"PeriodicalIF":4.6,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106004","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

A network traffic classification method based on comprehensive feature extraction and adaptive fusion networks 基于综合特征提取和自适应融合网络的网络流量分类方法

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-15 DOI: 10.1016/j.comnet.2025.111714

Shasha Zhao , Xiangnan Feng , Yiyao Tao , He Chen , Di Zhang , Dengyin Zhang

引用次数: 0

A survey on Identity and Access Management for future IoT services 未来物联网服务的身份和访问管理调查

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-15 DOI: 10.1016/j.comnet.2025.111718

Yiting Wang, Pedro Castillejo, José-Fernán Martínez-Ortega, Vicente Hernández Díaz

{"title":"A survey on Identity and Access Management for future IoT services","authors":"Yiting Wang, Pedro Castillejo, José-Fernán Martínez-Ortega, Vicente Hernández Díaz","doi":"10.1016/j.comnet.2025.111718","DOIUrl":"10.1016/j.comnet.2025.111718","url":null,"abstract":"<div><div>The explosive advancement of Artificial Intelligence (AI) and Edge Computing (EC) is accelerating the development of the future Internet of Things (IoT), which spans various application domains and has become an integral part of modern life. However, certain limitations of IoT introduce security and privacy challenges for users and enterprises, hindering its broader adoption. Identity and Access Management (IAM), capable of handling the massive scale of digital identities and permissions while ensuring that only authenticated entities can access authorized resources and interact securely, has been widely adopted as an entry point for securing IoT services. However, traditional IAM systems, primarily designed for cloud-based web services, face several challenges, such as scalability and privacy, when integrated into edge-native IoT architectures. This paper provides a systematic review of IAM solutions in IoT environments. It identifies four key requirements for future IoT services, analyzes IAM architecture and the state of the art of its six primary functionalities, namely storage, identity management, authentication, authorization, audit, and federation, and studies ten more comprehensive IAM solutions. A detailed evaluation of aspects such as functionality completeness, security, privacy, and scalability is carried out. Finally, based on the evaluation results, the missing points in the existing literature, as well as upcoming challenges and development trends, are pointed out. The study aims to inspire further research and development efforts towards building a comprehensive IAM solution for edge-enabled IoT systems.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111718"},"PeriodicalIF":4.6,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118201","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

CrossModal-CLIP: A novel multimodal contrastive learning framework for robust network traffic anomaly detection CrossModal-CLIP：一种用于鲁棒网络流量异常检测的新型多模态对比学习框架

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-15 DOI: 10.1016/j.comnet.2025.111723

Cheng Fang , Yingkun Liu , Shenglin Teng , Mingrui Yin , Tao Han

{"title":"CrossModal-CLIP: A novel multimodal contrastive learning framework for robust network traffic anomaly detection","authors":"Cheng Fang , Yingkun Liu , Shenglin Teng , Mingrui Yin , Tao Han","doi":"10.1016/j.comnet.2025.111723","DOIUrl":"10.1016/j.comnet.2025.111723","url":null,"abstract":"<div><div>The rapid proliferation of Internet-connected devices has amplified online activities but also escalated the complexity of network threats. Traditional methods relying on statistical and raw byte-based analysis often inadequately capture comprehensive behaviors of network traffic, leading to potential information loss. In this article, a novel method for network anomaly detection using cross-modal contrastive learning is proposed. By effectively fusing intermediate “multimodal” representation of traffic data-byte grayscale images and statistical sequences-via contrastive learning, our method enhances the robustness of traffic representation. Using a cross-modal Transformer encoder for fusion strengthens this representation, addressing the limitations of traditional methods. In contrastive learning, a dynamically increasing temperature coefficient is designed to adjust the pre-training model. Additionally, leveraging self-supervised contrastive learning reduces reliance on labeled samples while enhancing feature extraction capabilities. Extensive experiments on multiple real datasets validate the effectiveness of our method, demonstrating excellent performance with significant improvements in recall and precision compared to existing approaches. In addition, by the invariance mechanism of contrastive learning across scenarios, we have also applied the pre-trained model to the encrypted environment to explore the generalization performance.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111723"},"PeriodicalIF":4.6,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118203","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

PEZD: A practical and effective zero-delay defense against website fingerprinting PEZD：一个实用和有效的零延迟防御网站指纹

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-14 DOI: 10.1016/j.comnet.2025.111716

Hengheng Xiong, Dapeng Man, Huanran Wang, Jingwen Tan, Jiguang Lv, Wu Yang

{"title":"PEZD: A practical and effective zero-delay defense against website fingerprinting","authors":"Hengheng Xiong, Dapeng Man, Huanran Wang, Jingwen Tan, Jiguang Lv, Wu Yang","doi":"10.1016/j.comnet.2025.111716","DOIUrl":"10.1016/j.comnet.2025.111716","url":null,"abstract":"<div><div>Website Fingerprinting (WF) enables an attacker to infer which website a user is visiting by analyzing the side-channel information of network traffic, posing a serious threat to anonymous systems such as Tor. To mitigate this issue, numerous defenses have been proposed to resist WF attacks. However, many defenses incur high overhead, impeding their deployment. Moreover, some defenses rely on the impractical assumption that the defender knows prior knowledge of which website the user visits. In this paper, we propose a practical and effective lightweight WF defense, named PEZD. It hinders attackers from recognizing a website’s unique patterns by adding dummy packets with diverse distributions into traffic traces. In particular, PEZD is a website-agnostic defense that does not require knowledge of the website users are visiting and incurs only moderate overhead to effectively prevent attacks. Extensive experiments demonstrate that PEZD reduces the accuracy of state-of-the-art attacks from 97 % to 19 %–38 % while introducing zero latency overhead and only 48 % bandwidth overhead. Moreover, we show that PEZD remains effective for injecting dummy packets only on the client-side, simplifying the implementation of the defense.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111716"},"PeriodicalIF":4.6,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106434","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

Identity-based linearly homomorphic proxy signature scheme 基于身份的线性同态代理签名方案

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-13 DOI: 10.1016/j.comnet.2025.111703

Heng Guo , Kun Tian , Fengxia Liu , Zhiyong Zheng , Yanan Wang

引用次数: 0

Generating P4 data planes using LLMs 使用llm生成P4数据平面

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-13 DOI: 10.1016/j.comnet.2025.111709

Mihai-Valentin Dumitru, Vlad-Andrei Bădoiu, Alexandru M. Gherghescu, Costin Raiciu

{"title":"Generating P4 data planes using LLMs","authors":"Mihai-Valentin Dumitru, Vlad-Andrei Bădoiu, Alexandru M. Gherghescu, Costin Raiciu","doi":"10.1016/j.comnet.2025.111709","DOIUrl":"10.1016/j.comnet.2025.111709","url":null,"abstract":"<div><div>Over the past few years, Large Language Models (LLMs) have become the source of impressive results in code generation. However, most research focuses on widely adopted general-purpose programming languages, with little attention given to niche domain-specific languages (DSLs). This raises the question: do DSLs, such as P4, a data plane programming language, have a place in the LLM world?</div><div>The potential impact of generating DSL code could be tremendous. Automatically generating data plane code promises flexible networks that can quickly adapt to specific conditions at the lowest level. P4 is structurally simpler than general-purpose languages, but also offers a much smaller corpus of existing programs, thus setting up interesting challenges for deep-learning based code generation.</div><div>In this paper, we show that crafting a highly specialized P4 dataset with domain knowledge is sufficient to bootstrap P4 code generation through fine-tuning existing LLMs, even when they have not encountered P4 code during pre-training. We further document the process of creating a relevant benchmark to assess the proficiency of fine-tuned models in generating P4 code. Our evaluation shows that our fine-tuned models outperform much larger models in both syntactic correctness and semantic alignment.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111709"},"PeriodicalIF":4.6,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109816","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

Joint design of sub-channel assignment and power control in D2D aided cellular system: a novel GNN and DRL based approach D2D辅助蜂窝系统中子信道分配和功率控制的联合设计：一种基于GNN和DRL的新方法

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-13 DOI: 10.1016/j.comnet.2025.111708

Zhongyu Ma , Ning Zhang , Heng Zhang , Yan Zhang , Zhaobin Li , Qun Guo

{"title":"Joint design of sub-channel assignment and power control in D2D aided cellular system: a novel GNN and DRL based approach","authors":"Zhongyu Ma , Ning Zhang , Heng Zhang , Yan Zhang , Zhaobin Li , Qun Guo","doi":"10.1016/j.comnet.2025.111708","DOIUrl":"10.1016/j.comnet.2025.111708","url":null,"abstract":"<div><div>Device-to-Device (D2D) communication integrated with cellular networks is viewed as a promising network technology for enhancement of power efficiency and spectral utilization in the proximity-based wireless applications scenarios. However, co-channel interference caused by simultaneous sharing of wireless resources between the concurrent links including D2D links and cellular links poses a significant challenge for this system. To this end, a novel graph neural network (GNN) and deep reinforcement learning (DRL) combined resource allocation framework is proposed in this paper. Firstly, the joint design of sub-channel assignment and power control in the D2D overlapped cellular system is investigated as intractable nonlinear programming, where the long-term sum-of-rate (LSR) of cellular links and the transmission success rate (TSR) of D2D links are simultaneously maximized under the constraints such as concurrent interference and traffic demands, etc. Secondly, a GNN and DRL combined resource allocation framework (GD-CRAF) is proposed, where the GNN based graph sampling and aggregation (GraphSAGE) is designed to efficiently exploit the interference features from the incomplete global interference graph constructed with local interference, and the double deep Q-network (DDQN) based sub-channel assignment and power control is proposed under the DRL framework. Finally, the superiority of the proposed GD-CRAF framework is verified in diversified scenarios, where the convergence and effectiveness of the GD-CRAF are demonstrated. It is shown from the experimental results that the LSR and TSR of the GD-CRAF are superior to that of other references such as DQN based scheme, Q-Learning based scheme and random allocation based scheme.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111708"},"PeriodicalIF":4.6,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106437","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

Efficient key encapsulation mechanisms from noncommutative NTRU 非交换NTRU的有效密钥封装机制

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-13 DOI: 10.1016/j.comnet.2025.111704

Ali Raya , Vikas Kumar , Sugata Gangopadhyay , Aditi Kar Gangopadhyay

{"title":"Efficient key encapsulation mechanisms from noncommutative NTRU","authors":"Ali Raya , Vikas Kumar , Sugata Gangopadhyay , Aditi Kar Gangopadhyay","doi":"10.1016/j.comnet.2025.111704","DOIUrl":"10.1016/j.comnet.2025.111704","url":null,"abstract":"<div><div>Key Encapsulation Mechanisms (KEMs) are cryptographic set of algorithms used to establish a shared secret between two parties over an insecure channel. In the context of post-quantum cryptography, KEMs are typically constructed from hard mathematical problems believed to resist quantum attacks. Among these, lattice-based schemes–particularly those based on the NTRU problem–have been widely studied due to their efficiency and strong security foundations. Traditional NTRU constructions operate over commutative polynomial rings, offering a good balance between speed and compactness. However, recent efforts have proposed noncommutative variants of NTRU to enhance resistance against algebraic attacks. While these variants improve security properties, they generally fall short in terms of performance when compared to the original NTRU. This work introduces the first noncommutative NTRU construction that matches the performance of classical NTRU over the ring of integers. In addition, we propose a second design based on the ring of Eisenstein integers, further enhancing computational efficiency. We provide full KEM implementations of both constructions and benchmark them against existing commutative and noncommutative NTRU-based schemes. Our results demonstrate that the twisted dihedral group ring-based construction achieves encapsulation and decapsulation speeds on par with NTRU-HPS, while improving key generation speed by a factor of 2.5. The Eisenstein integer-based scheme shows an improvement of 1.6<span><math><mo>×</mo></math></span> in key generation and 1.3<span><math><mo>×</mo></math></span> in encapsulation and decapsulation. These findings confirm that noncommutative algebra can be leveraged effectively to achieve competitive performance in practical post-quantum KEM designs.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111704"},"PeriodicalIF":4.6,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109812","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

Data-driven resource allocation for ensuring remote data collection timeliness in integrated ground-air-space networks 数据驱动的资源分配，以确保地空一体化网络中远程数据采集的及时性

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-12 DOI: 10.1016/j.comnet.2025.111715

Jinsong Gui , Hanjian Liu

{"title":"Data-driven resource allocation for ensuring remote data collection timeliness in integrated ground-air-space networks","authors":"Jinsong Gui , Hanjian Liu","doi":"10.1016/j.comnet.2025.111715","DOIUrl":"10.1016/j.comnet.2025.111715","url":null,"abstract":"<div><div>Ensuring remote data collection timeliness without terrestrial network infrastructure support is a huge challenge. The exploration of addressing this challenge with the aid of opportunistic unmanned aerial vehicles (UAVs) and satellites has received extensive attention. In this paper, we address a data-driven resource allocation problem, which aims to ensure data collection timeliness, minimize communication resource waste, and maximize data collection amount under the UAVs’ opportunistic access mode and satellites’ random access mode. However, due to UAVs’ dynamic behaviors, time-varying data collection missions, real-time matching demand between ground nodes and UAVs, and free competition of UAV-satellite access resources, it will be difficult to achieve the above goal if it is considered as a global optimization problem. Thus, we construct three problems in turn that collectively describe the requirements of above goal, and then reformulate the first two problems as the Markov decision process models and take deep reinforcement learning tools to get the corresponding solutions, respectively. Next, the solution to the third problem is approximated by alternately invoking the algorithms of the first two problems. Finally, our simulation results are compared with those of other benchmark schemes from different perspectives, and the effectiveness and superiority of the presented solutions are verified.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111715"},"PeriodicalIF":4.6,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106440","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