Computer Networks最新文献

{"title":"Certificateless federated authentication and key agreement in IoV","authors":"Raghav ,&nbsp;Chanchal Maurya ,&nbsp;Shekhar Verma","doi":"10.1016/j.comnet.2026.112017","DOIUrl":"10.1016/j.comnet.2026.112017","url":null,"abstract":"<div><div>The increasing connectivity of IoV requires secure and efficient authentication techniques that ensure trusted communication between vehicles and service providers. Federated authentication and single sign on techniques are frequently used to facilitate user verification across multiple domains. However, these techniques are dependent on centralized entities and involve complex certificate management, making them vulnerable to key escrow problems, scalability challenges, and attacks such as impersonation, replay, and ESL. In addition, they introduce substantial computational and communication overhead, making them unsuitable for delay-sensitive vehicular environments. To overcome these limitations, this paper proposes the first certificateless federated authentication and key agreement scheme (CL-FAKA-IoV) for cross-domain IoV environments. The scheme is designed to enable efficient mutual authentication between vehicles and service providers without requiring the TA during real-time communication. The security of CL-FAKA-IoV is formally proven under the RoR model, demonstrating its resistance to cryptographic attacks such as impersonation, replay, and man-in-the-middle. Additionally, the protocol is validated using the AVISPA tool, confirming its robustness against adversaries. Informally, CL-FAKA-IoV guarantees critical security properties, including ESL resistance, KCI resistance, anonymity and unlinkability, as well as perfect forward and backward secrecy and replay protection. Performance evaluation results show that the proposed scheme significantly reduces execution time, communication cost, and memory overhead compared to existing federated authentication protocols, making it a practical and scalable solution for secure deployment in real-world IoV ecosystems.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112017"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039282","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":"LCC-AKA: Lightweight certificateless cross-domain authentication key agreement protocol for IoT devices","authors":"Yingjie Cai ,&nbsp;Tianbo Lu ,&nbsp;Jiaze Shang ,&nbsp;Yanfang Li ,&nbsp;Qitai Gong ,&nbsp;Hanrui Chen","doi":"10.1016/j.comnet.2026.112018","DOIUrl":"10.1016/j.comnet.2026.112018","url":null,"abstract":"<div><div>Authentication key agreement (AKA) protocol is an effective method for achieving secure communication between Internet of Things (IoT) devices. However, existing public key infrastructure-based and identity-based AKA protocols face limitations due to complex certificate management and key escrow issues. Furthermore, cross-domain communication is a fundamental requirement for IoT. However, current solutions addressing this challenge rely on trusted third parties, which undoubtedly increases the communication overhead and system complexity during the authentication phase. To address these challenges, we propose a new provably secure lightweight certificateless cross-domain authentication key agreement protocol (LCC-AKA). By introducing a certificateless public key cryptographic mechanism during the registration phase, we eliminate the need for complex certificate management and the limitations of key escrow, while also preventing insider attacks even under the semi-honest Key Generation Center (KGC) assumption. In the cross-domain authentication key agreement phase, we present a mechanism that enables direct cross-domain authentication and key agreement between devices without relying on trusted third parties, utilizing lightweight elliptic curve and hash function operations to achieve efficiency. In terms of security, we analyze the security vulnerabilities of existing certificateless cross-domain AKA schemes and extend the Real-Or-Random (ROR) model. The LCC-AKA protocol is provably secure under the extended ROR model and BAN logic. Security and performance analyses demonstrate that the LCC-AKA protocol can resist both insider and outsider attacks, including public key replacement attacks, while maintaining low computational and communication overhead.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112018"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039288","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":"CATER: Congestion aware trust-enabled routing for energy-constrained wireless sensor networks","authors":"Mahendra Kumar Jangir ,&nbsp;Karan Singh ,&nbsp;Tayyab Khan ,&nbsp;Ali Ahmadian","doi":"10.1016/j.comnet.2026.112030","DOIUrl":"10.1016/j.comnet.2026.112030","url":null,"abstract":"<div><div>Wireless Sensor Networks (WSNs) are essential in modern applications like environmental monitoring, industrial automation, and security. However, they suffer from pivotal issues of internal threats, congestion, and power constraint, crippling their efficiency and reliability. These threats include data manipulation and congestion, which degrade network performance. Addressing these challenges is crucial to ensure WSNs can maintain reliable operation while effectively managing energy resources and combating malicious activities. Thus, to address these limitations, this paper introduces CATER (Congestion Aware Trust-Enabled Routing), a new trust-based congestion-aware energy-constrained routing protocol for WSNs. CATER's primary contributions are: (1) an end-to-end multi-dimension trust evaluation model consisting of direct trust, indirect trust, energy trust, and an expected positive probability trust model for robust trust estimation; (2) an adaptive congestion control model for dynamically adjusting transmission rates according to real-time network status using the buffer capacity and queue length as variables; and (3) a trust-enabled routing module performing secure and efficient data transmission employing trusted sensor node selection. After trust evaluation, the proposed CATER protocol detects the congestion in the WSN. The congestion is detected using buffer capacity and queue length at a sensor node. Once congestion is detected at a node, the congested node sends a feedback message to the neighbor (source) node to optimize the transmission rate. The proposed CATER protocol always selects energy-efficient and trustworthy next-hop to transfer available data packets toward the sink. MATLAB simulations readily verify that CATER improves energy efficiency by 15.82%, packet drop ratio by 46.95%, and decreases end-to-end delay by 31.81% compared to other state-of-the-art existing routing protocols like CHicDra and SEFR. CATER also improves network throughput and packet delivery ratio (PDR) even in over-loaded and adversarial environments up to 50% adversarial nodes. The findings conclusively demonstrate CATER to be a very effective tool for providing efficient, reliable, and congestion-aware routing for WSNs with profound implications for real-world industrial and IoT applications.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112030"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039285","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":"Corrigendum to “Distributed quantum computing: A survey” [Computer Networks Volume 254 December 2024 110672]","authors":"Marcello Caleffi ,&nbsp;Michele Amoretti ,&nbsp;Davide Ferrari ,&nbsp;Jessica Illiano ,&nbsp;Antonio Manzalini ,&nbsp;Angela Sara Cacciapuoti","doi":"10.1016/j.comnet.2026.112079","DOIUrl":"10.1016/j.comnet.2026.112079","url":null,"abstract":"","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112079"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147398146","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":"Joint communication and sensing optimization for LEO-Multi-UAV SAGIN: Task offloading, resource allocation and UAV trajectory","authors":"Pengya Duan ,&nbsp;Wei Huang ,&nbsp;Yang Yang ,&nbsp;Guiyan Liu ,&nbsp;Fei Wang ,&nbsp;Yan Wu ,&nbsp;Xiongyu Zhong","doi":"10.1016/j.comnet.2026.112050","DOIUrl":"10.1016/j.comnet.2026.112050","url":null,"abstract":"<div><div>Space-Air-Ground Integrated Network (SAGIN) is a key architecture for achieving wide-area sensing and communication services. However, the connection between Low Earth Orbit (LEO) satellites and ground devices is constrained by satellite mobility and service angles. Unmanned Aerial Vehicles (UAVs), acting as relay and sensing nodes, can effectively bridge this gap. Nevertheless, under their limited onboard resources, the coupled impacts between UAV trajectory planning and the performance of communication and sensing-especially in scenarios where multi-UAV collaboration extends LEO service coverage-have not been fully investigated. To address these challenges, this paper proposes an integrated sensing and computation offloading architecture for SAGIN, where UAVs perform multi-target sensing while cooperating with LEO satellites to provide communication and computational services. We formulate a joint optimization problem that encompasses user offloading decisions, communication-sensing time allocation, UAV trajectory planning, and computing resource allocation, aiming to minimize long-term service latency. This problem is modeled as a mixed-integer nonlinear program (MINLP). To efficiently solve it, we develop a low-complexity Lyapunov-Benders Optimization (LBO) algorithm based on Lyapunov optimization and generalized Benders decomposition, which decomposes the long-term problem into tractable single-slot subproblems. Simulation results validate that the proposed method outperforms existing benchmarks in service latency, demonstrating its effectiveness in dynamic SAGIN environments.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112050"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090318","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":"SDRP-DQL: A satellite distributed routing protocol based on double deep Q-learning","authors":"Heng Du,&nbsp;Ligang Cong,&nbsp;Qingyun Liang,&nbsp;Shuyu Wang","doi":"10.1016/j.comnet.2026.112068","DOIUrl":"10.1016/j.comnet.2026.112068","url":null,"abstract":"<div><div>To address the routing challenges posed by dynamic topology and traffic imbalances in LEO satellite networks, this paper proposes a distributed intelligent routing algorithm, SDRP-DQL, based on DDQN. This algorithm achieves multi-dimensional state awareness and efficient routing decisions by deriving a reward mechanism with congestion trend prediction capabilities based on queuing theory and a distributed deep reinforcement learning framework, significantly optimizing network latency, packet loss rate, and load balancing. Experiments in a real satellite orbit simulation environment validate the superior performance of SDRP-DQL under different network sizes and complex traffic scenarios. Results show that compared with existing mainstream routing algorithms, SDRP-DQL achieves a 34.78% faster convergence speed, lower end-to-end latency and packet loss rate, and demonstrates good robustness and scalability in the face of node failures and link interruptions. This method provides technical support for intelligent routing in future large-scale satellite networks.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112068"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147398147","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":"Closed-Form Analytics of Multicell Massive MIMO System Using M-MMSE and TPE Techniques in Correlated Environment","authors":"Harleen Kaur,&nbsp;Ankush Kansal","doi":"10.1016/j.comnet.2025.111965","DOIUrl":"10.1016/j.comnet.2025.111965","url":null,"abstract":"<div><div>This work computes the average ergodic user rate for the multicell massive Multiple-Input Multiple-Output (mMIMO) system based on Multicell Minimum Mean Squared Error (M-MMSE) and Truncated Polynomial Expansion (TPE) techniques. By applying Random Matrix Theory (RMT) and large system analysis, the deterministic expression for the system's Signal-to-Interference plus Noise Ratio (SINR) with the M-MMSE scheme in uplink and downlink mode is computed, leading to the system's average user rate calculation. The M-MMSE scheme involves gram matrix inversion, increasing the system's lag and complexity. Therefore, the problem is solved by approximating the inverse of the matrix using TPE, which involves simple operations that can parallelize. Also, the complexity of the TPE technique depends only on the TPE order rather than the system's dimensions. Based on the RMT theory, the deterministic equivalents required for SINRs of the TPE scheme in uplink and downlink modes are derived. These deterministic equivalents for TPE SINRs are optimized to compute the average user rate for the system, matching the M-MMSE technique performance at a lower TPE order. In section 6, the system’s average user rate is validated by varying it with different parameters. The comparison between the M-MMSE and the TPE scheme shows that the TPE scheme achieves the required performance at J=3 TPE order. The theoretical results show the accuracy of derived deterministic equivalents.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 111965"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090323","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":"Incentive mechanism design in blockchain-based hierarchical federated learning over edge clouds","authors":"Xuanzhang Liu ,&nbsp;Jiyao Liu ,&nbsp;Xinliang Wei ,&nbsp;Yu Wang","doi":"10.1016/j.comnet.2026.112039","DOIUrl":"10.1016/j.comnet.2026.112039","url":null,"abstract":"<div><div>Federated learning (FL) is a promising distributed AI paradigm for protecting user privacy by training models on local devices (such as IoT devices). However, FL systems face challenges like high communication overhead and non-transparent model aggregation. To address these issues, integrating blockchain technology into hierarchical federated learning (HFL) to construct a decentralized, low latency, and transparent learning framework over a cloud-edge-client architecture has gained attention. To ensure participant engagement from edge servers and clients, this paper explores incentive mechanism design in a blockchain-based HFL system using a semi-asynchronous aggregation model. We model the resource pricing among clients, edge servers, and task publishers at the cloud as a three-stage Stackelberg game, proving the existence of a Nash equilibrium in which each participant could maximize their own utility. An iterative algorithm based on the alternating direction method of multipliers and backward induction is then proposed to optimize strategies. Extensive simulations verify the algorithm’s rapid convergence and demonstrate that our proposed mechanism consistently outperforms baseline strategies across various scenarios in terms of participant utilities. Our approach also achieves up to 7% higher model accuracy than baseline methods, confirming its practical effectiveness.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112039"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090326","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":"Efficient smart home message verification protocol based on Chebyshev chaotic mapping","authors":"Vincent Omollo Nyangaresi ,&nbsp;Mohd Shariq ,&nbsp;Daisy Nyang’anyi Ondwari ,&nbsp;Muhammad Shafiq ,&nbsp;Khalid Alsubhi ,&nbsp;Mehedi Masud","doi":"10.1016/j.comnet.2026.112033","DOIUrl":"10.1016/j.comnet.2026.112033","url":null,"abstract":"<div><div>Smart home networks deploy a myriad of sensors and intelligent devices to collect and disseminate massive and sensitive data, facilitating task automation for enhancing comfort, quality of life, efficiency, and sustainability. However, the utilization of public channels for interactions between users and smart home devices raises serious privacy and security issues. Numerous authentication schemes have been proposed in recent literature; most of them are prone to security attacks, including offline guessing, privileged insiders, and impersonation. In addition, some of them have complicated architectures that result in high resource consumption. In this paper, efficient Chebyshev polynomials and hashing functions are leveraged to develop a robust authentication protocol for smart homes. The Burrows–Abadi–Needham (BAN) logic-based detailed formal security analysis confirms the robustness of the joint authentication and key negotiation procedures. In addition, informal security analysis shows that the proposed protocol is secure against the Dolev-Yao (D-Y) and Canetti and Krawczyk (C-K) adversary models, mitigating several known security attacks. In terms of performance, the developed scheme incurs relatively low computation, energy, and communication costs.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112033"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090327","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":"ROAR: A resource-optimized adaptive routing protocol for underwater acoustic communication networks","authors":"Jinghua He ,&nbsp;Jie Tian ,&nbsp;Zhanqing Pu ,&nbsp;Yunan Zhu ,&nbsp;Wei Wang ,&nbsp;Haining Huang","doi":"10.1016/j.comnet.2026.112055","DOIUrl":"10.1016/j.comnet.2026.112055","url":null,"abstract":"<div><div>Underwater acoustic communication networks (UACNs) face significant challenges such as limited bandwidth, high attenuation, long latency, and time-varying channels. Most existing routing protocols rely on static resource configurations, which limits their performance in dynamic and resource-constrained underwater environments. To address these issues, this paper proposes a Resource-Optimized Adaptive Routing (ROAR) protocol that integrates dynamic relay selection with cross-layer resource optimization. ROAR improves forwarding efficiency by selecting appropriate forward nodes while excluding those with low residual energy. The optimal relay node is selected based on both residual energy and proximity to the destination. ROAR also formulates resource allocation as a multi-objective optimization problem, jointly considering transmission mode, subcarrier spacing, guard interval, and transmission power. The optimization aims to minimize energy consumption, reduce end-to-end delay, and improve bandwidth utilization. This problem is solved in real time using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), combined with the ideal point method, which dynamically adapts the resource configuration to the current network conditions during runtime. Simulation results indicate that ROAR outperforms Q-Learning-Based Energy-Efficient and Lifetime-Extended Adaptive Routing (QELAR), Reinforcement-Learning-Based Routing for Congestion Avoidance (RCAR), and Q-Learning-Based Hierarchical Routing Protocol (QHRP) in terms of average hop count, average end-to-end delay, and packet delivery ratio (PDR), highlighting its effectiveness in resource-constrained UACNs.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112055"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090330","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}