{"title":"Toward resilient communication architecture: Online network reconfiguration for UAV failure","authors":"Hao Yuan, Ruozhe Li, Laihe Wang, Bangbang Ren, Tao Chen, Deke Guo","doi":"10.1016/j.comnet.2025.111210","DOIUrl":"10.1016/j.comnet.2025.111210","url":null,"abstract":"<div><div>Given their flexible mobility, rapid deployment capabilities, and cost-effectiveness, unmanned aerial vehicles (UAVs) have recently emerged as a viable solution for providing computational services to distributed devices in the absence of terrestrial infrastructure. However, the vulnerability of the UAV hardware make them susceptible to failures caused by environmental factors and operational stresses, which would directly affect the communication services of these ground users. Therefore, to mitigate potential UAV failures, it is critical to develop a resilient communication architecture that optimizes the configuration of UAVs’ communication networks in an online manner. Consequently, we propose an online network reconfiguration method utilizing the Lyapunov optimization framework to dynamically adjust UAV trajectories and connectivity, thereby minimizing disruptions to communication services in the event of UAV failure. Evaluation results indicate that our proposed method significantly enhances system resilience. In comparison to baseline methods, the proposed method not only maintains high coverage utility and connectivity stability but also minimizes unnecessary UAV movements and operational time costs, thereby demonstrating its superiority.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"263 ","pages":"Article 111210"},"PeriodicalIF":4.4,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687204","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}
Computer NetworksPub Date : 2025-03-19DOI: 10.1016/j.comnet.2025.111220
Rui Xing, Zhenzhe Zheng, Qinya Li, Fan Wu, Guihai Chen
{"title":"MI-VFL: Feature discrepancy-aware distributed model interpretation for vertical federated learning","authors":"Rui Xing, Zhenzhe Zheng, Qinya Li, Fan Wu, Guihai Chen","doi":"10.1016/j.comnet.2025.111220","DOIUrl":"10.1016/j.comnet.2025.111220","url":null,"abstract":"<div><div>Vertical federated learning (VFL) allows multiple distributed clients with misaligned feature spaces to collaboratively accomplish global model training. Applying VFL to high-stakes decision services greatly requires model interpretation for decision reliability and diagnosis. However, the feature discrepancy in VFL raises new issues for model interpretation in distributed setting: one is from the local–global perspective, where the local importance of features is not equal to the global importance; and the other is from the local–local perspective, where information asymmetry among clients causes difficulty in identifying overlapped features. In this work, we propose a new distributed <u>M</u>odel <u>I</u>nterpretation method for <u>V</u>ertical <u>F</u>ederated <u>L</u>earning with feature discrepancy, namely MI-VFL. In particular, to deal with the local–global discrepancy, MI-VFL leverages the tools from probability theory and adversarial game theory to adjust the local importance of features and ensure the completeness of the selected features. To handle the local–local discrepancy, MI-VFL builds a federated adversarial learning model to efficiently identify the overlapped features at one time, rather than performing client-to-client intersections multiple times. We extensively evaluate MI-VFL on six synthetic datasets and five real-world datasets. The evaluation results reveal that MI-VFL can accurately identify the important features, suppress the overlapped features, and thus improve the model performance.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"263 ","pages":"Article 111220"},"PeriodicalIF":4.4,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687300","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}
Computer NetworksPub Date : 2025-03-18DOI: 10.1016/j.comnet.2025.111217
Yijie Shi , Kai Fan , Yuhan Bai , Chonglin Zhang , Kuan Zhang , Hui Li , Yintang Yang
{"title":"Blockchain-based anonymous and self-tallying voting with time-bounded ballot secrecy","authors":"Yijie Shi , Kai Fan , Yuhan Bai , Chonglin Zhang , Kuan Zhang , Hui Li , Yintang Yang","doi":"10.1016/j.comnet.2025.111217","DOIUrl":"10.1016/j.comnet.2025.111217","url":null,"abstract":"<div><div>Voting has been indispensable in modern society, encompassing activities from national public elections to board decision-making processes, highlighting the extensive utility of voting protocols. In cyberspace, electronic voting serves as a foundational protocol for many applications, facilitating decision-making, task execution, trust establishment, consensus achievement, and data validation. However, existing voting protocols face security and privacy challenges, including anonymity and fairness. To address these issues, we propose a novel secure and privacy-preserving voting protocol atop blockchain. Our protocol achieves all-time voter anonymity and full fairness. Meanwhile, we take advantage of delay encryption to achieve time-bounded ballot secrecy. In addition, our protocol supports robust self-tallying and traceability. The security analysis, coupled with performance evaluation, affirms that our protocol fulfills all intended security properties while maintaining a reasonable level of overhead.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"263 ","pages":"Article 111217"},"PeriodicalIF":4.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715572","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}
Computer NetworksPub Date : 2025-03-18DOI: 10.1016/j.comnet.2025.111209
Fang Yang, Tao Ma, Chunlai Ma, Nina Shu, Chao Chang, Chunsheng Liu, Tao Wu, Xingkui Du
{"title":"GenNP: A low-threshold and powerful network performance data generator","authors":"Fang Yang, Tao Ma, Chunlai Ma, Nina Shu, Chao Chang, Chunsheng Liu, Tao Wu, Xingkui Du","doi":"10.1016/j.comnet.2025.111209","DOIUrl":"10.1016/j.comnet.2025.111209","url":null,"abstract":"<div><div>The existing Discrete Event Simulators (DES) cannot meet the demands of modern networks for efficient, accurate, and flexible simulation. Recent <strong>m</strong>achine <strong>l</strong>earning models have demonstrated exceptional capabilities for <strong>e</strong>stimating <strong>n</strong>etwork <strong>p</strong>erformance (MLENP). However, the quality and quantity of available data greatly limit the accuracy and generalizability of ML models. After analyzing the data requirements of MLENP over the past decade and the shortcomings of existing DES, we propose a low-threshold and powerful <strong>n</strong>etwork <strong>p</strong>erformance data <strong>gen</strong>erator (GenNP), and generate a network performance dataset consisting of 10K samples. GenNP, with OMNeT++ and INET at its simulation core, integrates the configuration generation layer, simulation transformation layer, result extraction layer, and result output layer, achieving massive random generation of simulation configurations (networks, traffic, routing protocols, faults) and multi-granularity extraction of network performance data (throughput, drop, delay, jitter, routing table). We validate the robust capabilities of GenNP through a series of simulation experiments across multi-granularity (spatial, temporal), diversity (traffic models, network load, fault types, routing protocols), and efficiency (parallelism).</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"262 ","pages":"Article 111209"},"PeriodicalIF":4.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679702","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":"Lightweight authenticated key agreement scheme for IoMT network using generalized Chinese Remainder Theorem","authors":"Chandan Goswami , Aniket Basak , Rajeet Ghosh , Avishek Adhikari , Pinaki Sarkar","doi":"10.1016/j.comnet.2025.111212","DOIUrl":"10.1016/j.comnet.2025.111212","url":null,"abstract":"<div><div>Rapid advancement of the Internet of Things (IoT) is revolutionizing various sectors of our daily lives; healthcare being a prime beneficiary. Likelihood of viral infections among medical personnel has drastically decreased with the introduction of wireless monitoring platforms in the Internet of Medical Things (IoMT) network. Recent developments in wireless communications and computer systems have further enhanced the efficiency, security, and privacy of the entire healthcare industry. However, integrating IoT with electronic health (e-health) management systems presents several challenges, including secure communications over insecure channels, authentication, and key agreement among participating devices. This manuscript introduces a secure three-factor (user, medical server, and sensor device) lightweight mutual authenticated key agreement scheme (KAS) based on the Chinese Remainder Theorem (CRT) for an arbitrary number of co-primes in the IoMT network. We present a formal semantic security analysis of our proposed protocol using the Real-Or-Random (ROR) model for computational security. Moreover, simulation results using the Automated Validation of Internet Security Protocols and Applications (AVISPA) show that the proposed scheme is safe against well-known active and passive threats. Our proposed scheme is well-designed to perform efficiently, reducing both computation cost and communication cost. Finally, the proposed scheme has significant security advantages and performance benefits, making the scheme more efficient, secure, and robust compared to its state-of-the-art counterparts.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"263 ","pages":"Article 111212"},"PeriodicalIF":4.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687202","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}
Computer NetworksPub Date : 2025-03-17DOI: 10.1016/j.comnet.2025.111174
Mohammad Parsa Toopchinezhad, Mahmood Ahmadi
{"title":"Machine learning approaches for active queue management: A survey, taxonomy, and future directions","authors":"Mohammad Parsa Toopchinezhad, Mahmood Ahmadi","doi":"10.1016/j.comnet.2025.111174","DOIUrl":"10.1016/j.comnet.2025.111174","url":null,"abstract":"<div><div>Active Queue Management (AQM), a network-layer congestion control technique endorsed by the Internet Engineering Task Force (IETF), encourages routers to discard packets before the occurrence of buffer overflow. Traditional AQM techniques often employ heuristic approaches that require meticulous parameter adjustments, limiting their real-world applicability. In contrast, Machine Learning (ML) approaches offer highly adaptive, data-driven solutions custom to dynamic network conditions. Consequently, many researchers have adapted ML for AQM throughout the years, resulting in a wide variety of algorithms ranging from predicting congestion via supervised learning to discovering optimal packet-dropping policies with reinforcement learning. Despite these remarkable advancements, no previous work has compiled these methods in the form of a survey article. This paper presents the first thorough documentation and analysis of ML-based algorithms for AQM, in which the strengths and limitations of each proposed method are evaluated and compared. In addition, a novel taxonomy of ML approaches based on methodology is also established. The review is concluded by discussing unexplored research gaps and potential new directions for more robust ML-AQM methods.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"262 ","pages":"Article 111174"},"PeriodicalIF":4.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643851","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}
Computer NetworksPub Date : 2025-03-17DOI: 10.1016/j.comnet.2025.111213
Xiaoling Yu , Yuntao Wang , Xin Huang
{"title":"Quantum-resistant ring signature-based authentication scheme against secret key exposure for VANETs","authors":"Xiaoling Yu , Yuntao Wang , Xin Huang","doi":"10.1016/j.comnet.2025.111213","DOIUrl":"10.1016/j.comnet.2025.111213","url":null,"abstract":"<div><div>Vehicular ad-hoc networks (VANETs) can improve traffic management efficiency and driving safety to support the construction of Intelligent Transportation System. Privacy protection in VANETs is one of the challenges that cannot be ignored. To this end, the ring signature is a promising cryptographic primitive for providing privacy protection and authentication. However, in practical ring signature-based VANETs, secret keys of vehicle users used for signing are often exposed because of network attacks or careless use. So far, most predecessors do not guarantee security from secret key exposure. Moreover, many existing ring signature-based systems for VANETs are fragile under quantum computer attacks. In this paper, we construct the first forward secure ring signature scheme from lattices. Based on this scheme, we then design a ring signature-based authentication system for VANETs to guarantee privacy-preserving authentication, message integrity, forward security, and post-quantum security. Our scheme combines the binary tree and lattice basis delegation technique to realize a one-way key update mechanism, where secret keys are ephemeral and updated with generating nodes in the binary tree. Thus, the adversary cannot forge the past signature even if the users’ present secret keys are revealed, which can reduce the damage from key exposure. Furthermore, we give rigorous security proof under the hardness assumption of the underlying Small Integer Solution (SIS) problem in lattice-based cryptography to realize post-quantum security. Finally, we show simulation experiments and comparative analysis to evaluate its performance.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"262 ","pages":"Article 111213"},"PeriodicalIF":4.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642189","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}
Computer NetworksPub Date : 2025-03-17DOI: 10.1016/j.comnet.2025.111204
Oceane Bel , Mariam Kiran
{"title":"Simulators for quantum network modeling: A comprehensive review","authors":"Oceane Bel , Mariam Kiran","doi":"10.1016/j.comnet.2025.111204","DOIUrl":"10.1016/j.comnet.2025.111204","url":null,"abstract":"<div><div>Quantum network research is exploring new networking protocols, physics-based hardware and novel experiments to demonstrate how quantum distribution will work over large distances. Current work explores much of these concepts in simulations, that are developed to understand how quantum networking will be set up and researchers can experiment virtually. Exposing flaws in network designs, like unsustainable topologies, or develop protocols that efficiently utilize network resources, simulators can also help assess whether workloads are balanced across virtual machines in the network. However, much of these simulation models come without reliable verification methods, for testing performance in real deployments.</div><div>In this paper, we present a review of, to the best of our knowledge, currently used toolkits for modeling quantum networks. With these toolkits and standardized validation techniques, we can lay down the foundations for more accurate and reliable quantum network simulators.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"263 ","pages":"Article 111204"},"PeriodicalIF":4.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687298","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}
Computer NetworksPub Date : 2025-03-17DOI: 10.1016/j.comnet.2025.111205
Woo-Hyeok Jang, Seung-Jae Han
{"title":"Collision avoidance by mitigating uncertain packet loss in multi-hop wireless IoT networks","authors":"Woo-Hyeok Jang, Seung-Jae Han","doi":"10.1016/j.comnet.2025.111205","DOIUrl":"10.1016/j.comnet.2025.111205","url":null,"abstract":"<div><div>Multi-hop wireless relaying is an effective solution to provide connectivity to IoT devices in places that are difficult to reach. Spatial reuse for higher spectral efficiency by allowing simultaneous transmissions, however, causes self-interference unless transmissions are carefully coordinated. To solve this issue, recently, ML(Machine Learning)-based transmission scheduling has been explored in many literatures. Existing ML-based schemes, however, have limitation in that they do not account for the control overhead associated with schedule deployment and network state collection. In this paper, we propose a DRL (Deep Reinforcement Learning)-based TDMA scheduling scheme that aims to optimize network throughput and minimize energy consumption while avoiding collisions. More specifically, we use a Sequence-to-Sequence (S2S) neural network to compose the DRL policy. One of the key novelties of our scheme is that the schedule deployment is conducted sparsely to reduce the control overhead. This causes uncertainties due to the random packet losses, and we mitigate the uncertainties via a technique called redundant scheduling. Simulation results demonstrate that the proposed scheme is scalable and converges quickly, and it outperforms existing schemes under various network conditions.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"262 ","pages":"Article 111205"},"PeriodicalIF":4.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642190","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}
Computer NetworksPub Date : 2025-03-17DOI: 10.1016/j.comnet.2025.111208
Zhiming Chu , Guyue Li , Qingchun Meng , Haobo Li , Yuwei Zeng
{"title":"Defeating CSI obfuscation mechanisms: A study on unauthorized Wi-Fi Sensing in wireless sensor network","authors":"Zhiming Chu , Guyue Li , Qingchun Meng , Haobo Li , Yuwei Zeng","doi":"10.1016/j.comnet.2025.111208","DOIUrl":"10.1016/j.comnet.2025.111208","url":null,"abstract":"<div><div>The proliferation of Wi-Fi sensing technology has raised significant privacy concerns due to potential unauthorized environmental monitoring. As a typical countermeasure, the Channel State Information (CSI) fuzzer uses a time-varying filter at the transmitter to obfuscate CSI, allowing only legitimate receiver who has the pre-shared filter parameters as keys to restore the original CSI. In this work, we present SnoopFi, a framework enabling unauthorized reconstruction of environment-matching sensing signals from obfuscated CSI, even with limited training samples. SnoopFi acquires accurate raw CSI when attackers exploit security vulnerabilities to obtain keys. It can also generate a new base signal that reflect the physical environment for sensing when the attackers’ capabilities are limited. SnoopFi employs two strategies to negate the filter’s effects: (1) The attacker first attempts to guess the keys, and then it inverts the filter by modeling the nonlinear relationship between the filter’s response and the keys; (2) With multiple receiving antennas, the attacker utilizes the ratio of CSIs between different antennas to wipe off the filter effect. Once the obfuscation is removed, SnoopFi uses a few-shot learning technique for precise sensing of user localization with constrained training samples. The experimental results show that SnoopFi achieves localization accuracies of 91.79% and 92.05% under the two strategies, respectively, with an average of only 18 samples per class.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"263 ","pages":"Article 111208"},"PeriodicalIF":4.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687299","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}