Computer Networks最新文献

{"title":"Blockchain-based multiple auditing scheme against cheating owner in clouds","authors":"Jifang Wang ,&nbsp;Shangping Wang ,&nbsp;Duo Zhang ,&nbsp;Qian Zhang ,&nbsp;Yinjuan Deng","doi":"10.1016/j.comnet.2025.111214","DOIUrl":"10.1016/j.comnet.2025.111214","url":null,"abstract":"<div><div>Along with the commonplace of cloud outsourcing services, the problem of auditing the integrity of outsourced data without downloading has attracted much attention increasingly. However, in most existing auditing schemes, the audit only focuses on resisting undependable cloud server, rarely considers the problem of resisting cheating owner. An unreliable data owner may store the data not the same as it claimed for interest. Even worse, an undependable owner may deliver a sham message deliberately to avoid paying server for service or to cheat its deposit. To solve this problem, we propose a blockchain-based multiple auditable scheme against cheating owner by constructing a novel incremental structure, that allows for low computation and communication overheads, while providing a continuous natural flow of joint verification between storage parties over time. Specifically, our scheme is a two-way verification protocol that makes both parties consistently dependable. Besides, the incremental structure that uses a reversed recursive hash chain structure combined with blockchain and aggregate signature, makes our scheme more suitable for big data auditing. Smart contract is deployed to realize a central-free mechanism of rewards and penalties. The security analysis and simulation experiment demonstrate that the proposal is secure, dependable, efficient and practical.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"263 ","pages":"Article 111214"},"PeriodicalIF":4.4,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725553","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}

{"title":"Enabling technologies for Web 3.0: A comprehensive survey","authors":"Md Arif Hassan ,&nbsp;Mohammad (Behdad) Jamshidi ,&nbsp;Bui Duc Manh ,&nbsp;Nam H. Chu ,&nbsp;Chi-Hieu Nguyen ,&nbsp;Nguyen Quang Hieu ,&nbsp;Cong T. Nguyen ,&nbsp;Dinh Thai Hoang ,&nbsp;Diep N. Nguyen ,&nbsp;Nguyen Van Huynh ,&nbsp;Mohammad Abu Alsheikh ,&nbsp;Eryk Dutkiewicz","doi":"10.1016/j.comnet.2025.111242","DOIUrl":"10.1016/j.comnet.2025.111242","url":null,"abstract":"<div><div>Web 3.0 represents the next stage of Internet evolution, aiming to empower users with increased autonomy, efficiency, quality, security, and privacy. This evolution has the potential to democratize content access by leveraging advancements in cutting-edge enabling technologies. In this paper, we conduct an in-depth survey of enabling technologies in the context of Web 3.0, such as blockchain, semantic web, 3D interactive web, Metaverse, Virtual Reality (VR) and Augmented Reality (AR), Internet of Things (IoT) technology, and their roles in shaping Web 3.0. We commence by providing a comprehensive background of Web 3.0, including its concept, basic architecture, potential applications, and industry adoption. Subsequently, we examine recent breakthroughs in IoT, 5G, and blockchain technologies that are pivotal to Web 3.0 development. Following that, other enabling technologies, including AI, semantic web, and 3D interactive web, are discussed. Utilizing these technologies can effectively address the critical challenges in realizing Web 3.0, such as ensuring decentralized identity, platform interoperability, data transparency, reducing latency, and enhancing the system’s scalability. Finally, we highlight significant challenges associated with Web 3.0 implementation, emphasizing potential solutions and providing insights into future research directions in this field.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"264 ","pages":"Article 111242"},"PeriodicalIF":4.4,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738227","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}

{"title":"Edge-caching assisted underlay spectrum sharing in large-scale cognitive radio networks","authors":"Hao Dai ,&nbsp;Chao Zhai ,&nbsp;Jiachao Yu ,&nbsp;Jie Gao ,&nbsp;Jie Tian","doi":"10.1016/j.comnet.2025.111238","DOIUrl":"10.1016/j.comnet.2025.111238","url":null,"abstract":"<div><div>Edge-caching and spectrum sharing are promising techniques to meet the fast-growing wireless transmission requirements. In this paper, we propose an edge-caching based underlay spectrum sharing scheme for a large-scale cognitive radio network. In the primary system, primary users (PUs) request files from their associated base stations. In the secondary system, secondary transmitters (STs) intend to communicate with their receivers by sharing the spectrum, and secondary helpers (SHs) actively cache the files of primary system. In the device-to-device (D2D) communication range around each PU, the SH that has cached the file requested by the PU and has the shortest distance to the PU is selected for the cooperative file transfer. With the cooperation from SHs, the transmission quality towards PUs can be greatly improved, and STs can achieve more opportunities for the spectrum sharing. An optimization problem is formulated to maximize the area throughput of secondary system under the performance constraint of primary system. We propose a low-complexity CVX-SA algorithm by decomposing the original problem into two subproblems to jointly determine the file caching policy and system critical parameters. Numerical results show that, compared with the benchmark schemes, our proposed scheme can significantly improve the area throughput of the secondary system.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"263 ","pages":"Article 111238"},"PeriodicalIF":4.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734869","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}

{"title":"Mobility-aware decentralized federated learning with joint optimization of local iteration and leader selection for vehicular networks","authors":"Dongyu Chen ,&nbsp;Tao Deng ,&nbsp;Juncheng Jia ,&nbsp;Siwei Feng ,&nbsp;Di Yuan","doi":"10.1016/j.comnet.2025.111232","DOIUrl":"10.1016/j.comnet.2025.111232","url":null,"abstract":"<div><div>Federated learning (FL) emerges as a promising approach to empower vehicular networks, composed by intelligent connected vehicles equipped with advanced sensing, computing, and communication capabilities. While previous studies have explored the application of FL in vehicular networks, they have largely overlooked the intricate challenges arising from the mobility of vehicles and resource constraints. In this paper, we propose a framework of mobility-aware decentralized federated learning (MDFL) for vehicular networks. In this framework, nearby vehicles train an FL model collaboratively, yet in a decentralized manner. We formulate a local iteration and leader selection joint optimization problem (LSOP) to improve the training efficiency of MDFL. For problem solving, we first reformulate LSOP as a decentralized partially observable Markov decision process (Dec-POMDP), and then develop an effective optimization algorithm based on multi-agent proximal policy optimization (MAPPO) to solve Dec-POMDP. Finally, we verify the performance of the proposed algorithm by comparing it with other algorithms.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"263 ","pages":"Article 111232"},"PeriodicalIF":4.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734870","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}

{"title":"Attack-adaptive network intrusion detection systems for IoT networks through class incremental learning","authors":"Francesco Cerasuolo,&nbsp;Giampaolo Bovenzi,&nbsp;Domenico Ciuonzo,&nbsp;Antonio Pescapè","doi":"10.1016/j.comnet.2025.111228","DOIUrl":"10.1016/j.comnet.2025.111228","url":null,"abstract":"<div><div>The advent of the Internet of Things (IoT) has ushered in an era of unprecedented connectivity and convenience, enabling everyday objects to gather and share data autonomously, revolutionizing industries, and improving quality of life. However, this interconnected landscape poses cybersecurity challenges, as the expanded attack surface exposes vulnerabilities ripe for exploitation by malicious actors. The surge in network attacks targeting IoT devices underscores the urgency for <em>robust</em> and <em>evolving</em> security measures. Class Incremental Learning (CIL) emerges as a dynamic strategy to address these challenges, empowering Machine Learning (ML) and Deep Learning (DL) models to adapt to evolving threats while maintaining proficiency in detecting known ones. In the context of IoT security, characterized by the constant emergence of novel attack types, CIL offers a powerful means to enhance Network Intrusion Detection Systems (NIDS) resilience and network security. This paper aims to investigate how CIL methods can support the evolution of NIDS within IoT networks (<span><math><mi>i</mi></math></span>) <em>by evaluating both attack detection and classification tasks</em>— optimizing hyperparameters associated with the incremental update or to the traffic input definition—and (<span><math><mrow><mi>i</mi><mi>i</mi></mrow></math></span>) <em>by addressing also key research questions related to real-world NIDS challenges</em>—such as the explainability of decisions, the robustness to perturbation of traffic inputs, and scenarios with a scarcity of new-attack samples. Leveraging <em>4 recently-collected and comprehensive IoT attack datasets</em>, the study aims to evaluate the effectiveness of CIL techniques in classifying 0-day attacks.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"263 ","pages":"Article 111228"},"PeriodicalIF":4.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A blockchain-based medical IoT authentication scheme resistant to combined attacks","authors":"Ziwen Wang ,&nbsp;Yajun Guo ,&nbsp;Yimin Guo","doi":"10.1016/j.comnet.2025.111241","DOIUrl":"10.1016/j.comnet.2025.111241","url":null,"abstract":"<div><div>The Medical Internet of Things (MIoT) has transformed the healthcare industry by facilitating telemedicine and real-time health monitoring. In MIoT, doctors can address patients’ issues at any time and in any scenario. However, MIoT faces common data security issues in IoT applications, and the unique nature of healthcare services demands higher privacy protection. Consequently, ensuring secure communication in MIoT is imperative. Traditional MIoT Authentication and Key Agreement (AKA) protocols often use centralized methods, presenting a single point of failure. Moreover, these protocols can only resist single attacks and cannot cope with combined attacks that attackers might launch. These limitations make it difficult to meet the actual needs of MIoT. To address these issues, we propose an MIoT authentication protocol that resists combined attacks and solves single points of failure by integrating Physical Unclonable Functions (PUF), blockchain technology, and Elliptic Curve Cryptography (ECC) while introducing fog computing. Security analysis demonstrates that the proposed protocol ensures semantic security and satisfies the specified security requirements even under combined attacks. Performance analysis indicates that our protocol achieves more comprehensive security features under combined attacks and has lower consumption in several aspects.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"263 ","pages":"Article 111241"},"PeriodicalIF":4.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715569","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}

{"title":"Memory-efficient programmable packet parsing for multi-tenant terabit networks","authors":"Xuetan Cheng ,&nbsp;Yingwen Chen ,&nbsp;Xiangrui Yang,&nbsp;Huan Zhou,&nbsp;Lailong Luo,&nbsp;Deke Guo","doi":"10.1016/j.comnet.2025.111240","DOIUrl":"10.1016/j.comnet.2025.111240","url":null,"abstract":"<div><div>Programmable data plane architectures such as RMT and dRMT obtain great attention due to their flexibility in processing packets on demand without modifying the switch chip design. Unfortunately, the packet parser, as a crucial component, suffers from low processing performance and large logic usage. Existing programmable packet parser design utilizes a Finite State Machine (FSM) to parse the packet header vector (PHV) in a loop manner, or enumerates all possible protocol paths to extract the packet header vector in parallel, which leads to low throughput or significant consumption of T-CAM resources.</div><div>This paper proposes the partition parser (PParser), a novel programmable parser design, working in multi-tenant networks, that makes the best trade-offs between the parsing performance and the resource usage as far as we are concerned. To maximize the performance, PParser initiates the protocol path analysis in compile-time and parses packets in parallel using T-CAM. To avoid the path explosion without reducing performance, PParser efficiently partitions the parsing graph into sub-graphs and leverages a multi-stage T-CAM for cascade parsing. The performance, flexibility, and resource usage of PParser are excessively evaluated using real-world protocols on the FPGA prototype. The result shows that PParser achieves 3.98<span><math><mo>×</mo></math></span> throughput compared with the FSM-based parser and 87% compression rate and a similar throughput compared with HyperParser.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"264 ","pages":"Article 111240"},"PeriodicalIF":4.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748078","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}

{"title":"Delay-energy-aware joint multi-cell association, service caching, and task offloading in hybrid-task heterogeneous edge computing networks","authors":"Bassant Tolba ,&nbsp;Maha Elsabrouty ,&nbsp;Mohammed Abo-Zahhad ,&nbsp;Akira Uchiyama ,&nbsp;Ahmed H. Abd El-Malek","doi":"10.1016/j.comnet.2025.111231","DOIUrl":"10.1016/j.comnet.2025.111231","url":null,"abstract":"<div><div>In highly dense networks with huge computational requirements, mobile edge computing has been proposed to alleviate network traffic congestion and reduce system latency by offloading the intensive computational tasks to the network edges for execution. As a result, achieving low energy consumption and reduced system latency has become increasingly important under this paradigm. In this paper, we propose a delay-energy-aware algorithm for minimizing the overall system latency, energy consumption and balancing the load among base stations, particularly in the case of hybrid-task scenarios. A novel crafted weighted-sum objective function for the total system latency and energy consumption is designed to formulate a non-convex joint optimization problem. The Gibbs sampling algorithm is used to solve the formulated optimization problem through updating the caching and offloading decision variables. The proposed framework investigates the optimal multi-cell association, power allocation, service data caching, and computational task offloading for multi-tier communication and edge computing networks. The effect of limited quota on multi-tier heterogeneous networks is investigated under Rayleigh fading channels. Simulation results demonstrate the superiority of the proposed algorithms over the state-of-the-art works in terms of reducing the system latency and energy consumption.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"263 ","pages":"Article 111231"},"PeriodicalIF":4.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715570","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}

{"title":"Multi-channel real-time access with starvation avoidance for heterogeneous data in smart factories","authors":"Huaguang Shi ,&nbsp;Jian Huang ,&nbsp;Hengji Li ,&nbsp;Tianyong Ao ,&nbsp;Wei Li ,&nbsp;Yi Zhou","doi":"10.1016/j.comnet.2025.111236","DOIUrl":"10.1016/j.comnet.2025.111236","url":null,"abstract":"<div><div>In Industrial Wireless Control Networks (IWCNs), Industrial Devices (IDs) generate massive amounts of Data Packets (DPs) with different Quality of Service (QoS) requirements. However, most of the existing works set different priorities for differentiated transmission of heterogeneous data, and the high-priority DPs will access the channel immediately after they are generated. This may result in the access starvation of low-priority DPs in time-frequency resource-constrained IWCNs. In this paper, we study the collaborative transmission algorithm of heterogeneous data to avoid access starvation for lower-priority DPs while guaranteeing QoS for higher-priority DPs. Specifically, we first design an edge-assisted learning architecture with multi-access edge computing to assist the training of the algorithm. Then, to mitigate access conflicts among IDs, a gated recurrent unit enhanced Multi-Agent Deep Reinforcement Learning (MADRL) framework was adopted. Based on the framework, we propose a Multi-criteria Decision based dynamic Multi-channel Access (MDMA) algorithm, where high-priority DPs can consider waiting for access according to their own criteria to avoid preempting the channel access opportunity of low-priority DPs approaching the deadline. Extensive simulations show that the proposed MDMA algorithm outperforms the existing algorithms in terms of the average channel utilization rate and the average completion rate of heterogeneous data.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"264 ","pages":"Article 111236"},"PeriodicalIF":4.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748011","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}

{"title":"GEN-DRIFT: Generative AI-driven drift handling for beyond 5G networks","authors":"Venkateswarlu Gudepu ,&nbsp;Bhargav Chirumamilla ,&nbsp;Venkatarami Reddy Chintapalli ,&nbsp;Piero Castoldi ,&nbsp;Luca Valcarenghi ,&nbsp;Bheemarjuna Reddy Tamma ,&nbsp;Koteswararao Kondepu","doi":"10.1016/j.comnet.2025.111237","DOIUrl":"10.1016/j.comnet.2025.111237","url":null,"abstract":"<div><div>Beyond fifth-generation (B5G) networks enable high data rates, low latency, and massive machine communications, driving digital transformation across sectors. The integration of Artificial Intelligence and Machine Learning (AI/ML) technologies plays a vital role in enhancing the performance and efficiency of B5G networks. However, the dynamic and ever-evolving service demands associated with B5G use cases lead to the occurrence of drift, which can significantly degrade the performance of AI/ML models. Drift occurrence often results in violations of Service Level Agreements (SLAs) and over- or under-provisioning of resources, ultimately impacting user experience and network reliability.</div><div>Drift detection and adaptation are essential for addressing the dynamic service demands of B5G networks. Existing threshold approach and various other frameworks, have significant limitations, — SLA violations from delayed drift detection and inefficient resource management due to frequent retraining. This paper proposes a drift handling framework that determines drift promptly after its occurrence using Generative Artificial Intelligence (Gen-AI). The proposed Gen-AI framework is evaluated for a Quality of Service Prediction use case on the Open Radio Access Network (O-RAN) Software Community (OSC) platform and compared to the existing threshold and other frameworks. Also, a real-time dataset from the Colosseum testbed is considered to evaluate the Network Slicing (NS) use case with the proposed Gen-AI framework for drift handling.</div><div>The results demonstrate that the proposed Gen-AI framework leverages both Generative Adversarial Network (GAN) and Variational AutoEncoder (VAE), significantly enhances drift detection and adaptation time in B5G networks. Specifically, in the QoS prediction use case, GAN achieves 98% drift detection accuracy, while the VAE achieves 95% , compared to 85% for the classifier framework, 25% for the threshold-based approach. In addition, a similar kind of results is observed in case of the network slicing use case. These results highlight the effectiveness of the proposed Gen-AI framework in proactively handling drift with reduced detection and adaptation time, making it a promising solution for B5G networks.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"263 ","pages":"Article 111237"},"PeriodicalIF":4.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143706246","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}