Computer Networks最新文献_第9页

A blockchain-based federated learning framework against poisoning attacks in the internet of vehicles 基于区块链的联合学习框架，防止车联网中的中毒攻击

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-11 DOI: 10.1016/j.comnet.2025.111705

Irshad Ullah, Xiaoheng Deng, Xinjun Pei, Husnain Mushtaq, Muhammad Uzair, Shazib Qayyum

{"title":"A blockchain-based federated learning framework against poisoning attacks in the internet of vehicles","authors":"Irshad Ullah, Xiaoheng Deng, Xinjun Pei, Husnain Mushtaq, Muhammad Uzair, Shazib Qayyum","doi":"10.1016/j.comnet.2025.111705","DOIUrl":"10.1016/j.comnet.2025.111705","url":null,"abstract":"<div><div>Federated Learning (FL) offers a decentralized solution for training machine learning models across distributed devices, making it well-suited for the Internet of Vehicles (IoV), where large volumes of sensitive data are generated. Despite this, FL systems are susceptible to poisoning attacks, which can compromise model integrity and performance. To address these challenges, this paper proposes SPBFL-IoV, a secure and privacy-preserving blockchain-based federated learning framework for IoV environments. The framework is specifically designed to defend against poisoning attacks, such as label-flipping and model manipulation. The proposed framework integrates blockchain technology to securely record model updates in a tamper-proof and auditable ledger, ensuring their integrity and verifiability. In addition, Homomorphic Encryption (HE) is employed to protect the confidentiality of data and model parameters during communication. Furthermore, to preserve the robustness, accuracy, and integrity of the global model in the presence of malicious participants, we employ advanced Filtering and Clipping mechanisms to identify and mitigate malicious updates. Experimental results demonstrate the effectiveness of SPBFL-IoV in terms of Overall Accuracy (All-Acc), Source-class Accuracy (Src-Acc), and Attack Success Rate (ASR), achieving an All-Acc of 98.10 % and Src-Acc of 96.00 % on the MNIST dataset, and an All-Acc of 76.15 % and Src-Acc of 60.10 % on the CIFAR-10 dataset. Furthermore, it maintains a low ASR of 0.39 % on MNIST and 9.23 % on CIFAR-10. Compared to existing methods, these results demonstrate the framework’s superior capability in countering poisoning attacks. Overall, the framework maintains high performance as measured by All-Acc and Src-Acc, and resilience against adversarial behavior, as reflected in its low ASR, making it a trustworthy solution for secure and collaborative learning within the IoV.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111705"},"PeriodicalIF":4.6,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106010","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

TOPLDM: Towards dynamic low overhead traffic obfuscation based on packet length distribution modification TOPLDM：基于分组长度分布修改的动态低开销流量混淆

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-11 DOI: 10.1016/j.comnet.2025.111707

Zhichao Hu , Likun Liu , Jiaxing Gong , Yao Zhang , Minghao Guo , Mengmeng Ge , Qing Guo , Lina Ma , Xiangzhan Yu

{"title":"TOPLDM: Towards dynamic low overhead traffic obfuscation based on packet length distribution modification","authors":"Zhichao Hu , Likun Liu , Jiaxing Gong , Yao Zhang , Minghao Guo , Mengmeng Ge , Qing Guo , Lina Ma , Xiangzhan Yu","doi":"10.1016/j.comnet.2025.111707","DOIUrl":"10.1016/j.comnet.2025.111707","url":null,"abstract":"<div><div>The emergence of encrypted traffic fingerprinting has made it possible to monitor and analyze users’ online activities even under encrypted protocols like SSL/TLS, posing a serious threat to the personal privacy and data security. While researchers have proposed various traffic obfuscation methods to defend against encrypted traffic fingerprinting, there are still issues such as the high resource overhead, the weak robustness, the difficulty in dynamically adjusting obfuscation strategies and the inability to deploy in real network environments. To address these problems, this paper proposes an efficient and effective traffic obfuscation method based on packet length distribution modification. It designs a distribution-based packet length mapping method to dynamically adjust the mapping rules of packet lengths by selecting different target distributions. The packets are then modified by segmentation and stacking. By modifying the distribution of packet lengths, this method indirectly affects temporal features, effectively resisting encrypted traffic fingerprinting methods. Experimental results show that the approach outperforms existing traffic obfuscation methods in terms of obfuscation effectiveness, with 7 % success rate improved in real traffic obfuscation. Additionally, through comparative experiments with classic methods such as BuFLO, Cs-BuFLO, WTF-PAD, FRONT, Wfd-GAN, WGAN, and FGSM-AS, the advantages of this method in terms of time and bandwidth resource consumption are verified, and showing satisfactory robustness towards retrain.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111707"},"PeriodicalIF":4.6,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106003","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

Novel packet management strategy for minimizing AoI in vehicle-to-everything communications 最小化车对物通信中AoI的新颖数据包管理策略

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-11 DOI: 10.1016/j.comnet.2025.111706

Saber F. Mohammed , Pan Zhiwen , Zeyad A.H. Qasem

{"title":"Novel packet management strategy for minimizing AoI in vehicle-to-everything communications","authors":"Saber F. Mohammed , Pan Zhiwen , Zeyad A.H. Qasem","doi":"10.1016/j.comnet.2025.111706","DOIUrl":"10.1016/j.comnet.2025.111706","url":null,"abstract":"<div><div>Real-time information freshness is critical for ensuring timely status updates in applications such as vehicle-to-everything (V2X) communications and autonomous driving. The age of information (AoI) metric is valuable for evaluating the freshness of delivered packets. However, maintaining low AoI is challenging due to limited bandwidth, computational delays, and stringent freshness requirements. To address these challenges, this paper proposes a novel packet management strategy, called age-priority last-generated first-served (AP-LGFS) for a multi-road user system operating over a cellular network. AP-LGFS dynamically prioritizes newly arrived packets and selectively preempts ongoing transmissions when incoming packets exhibit a lower expected AoI, ensuring the timely delivery of critical updates. Then, the proposed AP-LGFS is combined with queuing model to analyze both AoI and peak AoI (PAoI) in road user-to-vehicle communication links. Additionally, it investigates the impact of road user packet arrival rates on information freshness. We use a stochastic process to compare our strategy with other scheduling strategies within the solution space. Comparative simulations demonstrate that AP-LGFS outperforms other scheduling strategies in minimizing AoI and PAoI, thereby enhancing information freshness, and supporting reliable V2X communication systems.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111706"},"PeriodicalIF":4.6,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106009","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 and secure multiparty summation without semi-honest third-party 高效、安全的多方汇总，不需要半诚实的第三方

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-11 DOI: 10.1016/j.comnet.2025.111690

Zhuo Liu , Fulin Li , Mu Han , Shixin Zhu

引用次数: 0

Joint trajectory and offloading optimization in UAV-assisted MEC via federated multi-agent reinforcement learning and potential fields 基于联合多智能体强化学习和势场的无人机辅助MEC联合轨迹与卸载优化

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-10 DOI: 10.1016/j.comnet.2025.111681

Cong Wang , Ke Liu , Ying Yuan , Sancheng Peng , Guorui Li

{"title":"Joint trajectory and offloading optimization in UAV-assisted MEC via federated multi-agent reinforcement learning and potential fields","authors":"Cong Wang , Ke Liu , Ying Yuan , Sancheng Peng , Guorui Li","doi":"10.1016/j.comnet.2025.111681","DOIUrl":"10.1016/j.comnet.2025.111681","url":null,"abstract":"<div><div>Unmanned Aerial Vehicles (UAVs) assisted mobile edge computing (MEC) is characterized by flexible deployment, high mobility, and dynamic coverage. It facilitates an efficient execution of latency-sensitive tasks in scenarios such as emergency rescue and dynamic computility support, thereby demonstrating significant application prospect. However, joint scheduling of computility and task is still an open issue in optimizing task efficiency and UAVs’ energy consumption. To address this problem, we propose an UAV-assisted MEC framework based on federated multi-agent reinforcement learning (MARL) and potential fields (PF), which jointly optimizes UAV trajectories and task offloading strategies to minimize age of information (AoI) under latency and energy constraints. The decision-making process of multiple UAVs is to be modeled as a Partially Observable Markov Decision Process (POMDP) and to be solved by using a distributed federated MARL architecture. An adaptive federated collaboration model is designed for periodic parameter sharing based on credit allocation to enhance UAV collaboration and to alleviate partial observability. Additionally, a deep reinforcement learning (DRL) trajectory planning algorithm based on PF to enhance agents’ environment perception and decision-making ability. Experimental results show the effectiveness and feasibility of our proposed framework. It outperforms several existing RL-based approaches in terms of data freshness, task efficiency, and other key metrics while demonstrating strong adaptability in dynamic and complex MEC environments.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111681"},"PeriodicalIF":4.6,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049709","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

From latency bottlenecks to seamless edge: AD3PG-powered joint optimization of UAV trajectory and task offloading 从延迟瓶颈到无缝边缘：ad3pg驱动的无人机轨迹和任务卸载联合优化

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-10 DOI: 10.1016/j.comnet.2025.111700

Yitian Wang , Hui Wang , Jingfang Ding , Haibin Yu

{"title":"From latency bottlenecks to seamless edge: AD3PG-powered joint optimization of UAV trajectory and task offloading","authors":"Yitian Wang , Hui Wang , Jingfang Ding , Haibin Yu","doi":"10.1016/j.comnet.2025.111700","DOIUrl":"10.1016/j.comnet.2025.111700","url":null,"abstract":"<div><div>This paper addresses latency challenges in cloud-based task offloading caused by geographical server-user disparities by integrating Unmanned Aerial Vehicles (UAVs) with Mobile Edge Computing (MEC). We propose a dynamic UAV-assisted framework that optimizes real-time parameter adjustments to minimize system latency. Key challenges include joint task offloading, UAV trajectory optimization, and User Equipment (UE) occlusion detection under mobility constraints. To resolve these, we transform the problem into a Markov Decision Process (MDP) and develop an enhanced Adaptive Delayed Deep Deterministic Policy Gradient (AD3PG) algorithm, which improves upon DDPG by incorporating delayed updates and neural network tuning. The algorithm dynamically optimizes three critical aspects: UAV-UE connectivity establishment, occlusion-aware dual noise power configuration, and adaptive task offloading ratios. Extensive simulations demonstrate AD3PG’s superiority over baselines such as DDPG and Twin-Delayed DDPG (TD3) in reducing total system latency by 13.2–35.3 % under dynamic scenarios (e.g., 8 UEs with 100MB total task volume). Specifically, AD3PG achieves a task completion delay of 83.5–88 s across varying UE quantities, outperforming DDPG (89–115 s) and TD3 (87–95 s). These results validate the proposed framework’s efficacy for latency-sensitive applications in UAV-MEC systems.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111700"},"PeriodicalIF":4.6,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106011","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

Energy efficient resource allocation and trajectory optimization method for secure digital twin-enabled UAV-assisted MEC in 6G networks 6G网络中安全数字双启用无人机辅助MEC的节能资源分配和轨迹优化方法

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-10 DOI: 10.1016/j.comnet.2025.111679

Varun Kumar , Ishan Budhiraja , Akansha Singh , Sahil Garg , Georges Kaddoum , Mohammad Mehedi Hassan

{"title":"Energy efficient resource allocation and trajectory optimization method for secure digital twin-enabled UAV-assisted MEC in 6G networks","authors":"Varun Kumar , Ishan Budhiraja , Akansha Singh , Sahil Garg , Georges Kaddoum , Mohammad Mehedi Hassan","doi":"10.1016/j.comnet.2025.111679","DOIUrl":"10.1016/j.comnet.2025.111679","url":null,"abstract":"<div><div>The future sixth generation (6G) mobile network will be a highly heterogeneous system that integrates diverse technologies and communication paradigms, encompassing diverse consumer electronics devices, including various internet of things (IoT) devices utilizing different protocols. The combination of unmanned aerial vehicles (UAVs) and mobile edge computing (MEC) with 6G has created ground-breaking prospects for effective data processing and computation services in the IoT. Despite this improvement, the presence of an eavesdropper introduces significant security risks into the computing process of mobile devices (MDs), permitting the collection of sensitive data from MDs and perhaps affecting the correctness of offloaded computations. This study proposes an efficient technique for reducing energy usage in a secure digital twin (DT)-enabled UAV-assisted MEC metaverse network that faces the threat of a UAV eavesdropper. By ensuring the secure processing of all MDs data, the network meets its energy consumption objectives by optimizing trajectories and resources, taking into account parameters like as time, local computation, and offloading computation dispersion. Because of the complicated arrangement of the interplay of various variables and non-linear constraints, solving the problem directly is extremely difficult. To solve this complexity, an auxiliary variable is used to rearrange the problem into a more understandable format. We employ DT-enabled DRL to address this issue because traditional methods are inadequate. The empirical findings indicate that the proposed methodology achieved a reduction in energy consumption of approximately 83.32% and a decrease in time delay of roughly 11.97%, in comparison to the prevailing baseline methodologies.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111679"},"PeriodicalIF":4.6,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106439","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

Fast adaptation of multi-cell NOMA resource allocation via federated meta-reinforcement learning 基于联合元强化学习的多单元NOMA资源分配快速适应

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-10 DOI: 10.1016/j.comnet.2025.111701

Giang Minh Nguyen , Derek Kwaku Pobi Asiedu , Ji-Hoon Yun

{"title":"Fast adaptation of multi-cell NOMA resource allocation via federated meta-reinforcement learning","authors":"Giang Minh Nguyen , Derek Kwaku Pobi Asiedu , Ji-Hoon Yun","doi":"10.1016/j.comnet.2025.111701","DOIUrl":"10.1016/j.comnet.2025.111701","url":null,"abstract":"<div><div>Radio resource allocation in multi-cellular systems, particularly with non-orthogonal multiple access (NOMA), must be carefully optimized based on real-time user and network conditions, such as channel responses, user population, and inter-cell interference patterns, which naturally fluctuate over time. Fixed machine learning models for radio resource allocation often fail to adapt to these dynamic conditions, leading to suboptimal resource allocation. Moreover, such models struggle to handle inputs and outputs of varying dimensions, limiting their scalability and generalization in time-varying resource allocation problems. To address these challenges, we propose a novel multi-cell, multi-subband NOMA radio resource allocation solution that integrates meta-learning and federated learning (FL) with multi-agent reinforcement learning (MARL). Our solution maximizes energy efficiency (EE) by enabling one-shot adaptation to environmental variations and dynamically managing information dimensionality through the instantiation and removal of agents from a pretrained model. Under this framework, power allocation (PA) and subband allocation (SA) are jointly optimized in a two-stage process: the first stage employs a central reinforcement learning (RL) agent to solve the PA subproblem, while the second stage leverages multi-agent meta-RL combined with FL to address the SA subproblem. Evaluation results demonstrate that our solution effectively adapts to dynamic environments, including variations in channel conditions due to path loss and Doppler effects, as well as fluctuations in the user set. Notably, our approach consistently outperforms the benchmark algorithms, highlighting its robustness and superior adaptability.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111701"},"PeriodicalIF":4.6,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106005","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 comprehensive literature review of cyber threats and vulnerabilities in IoT-driven satellite networks: Research challenges and future directions 物联网卫星网络中网络威胁和漏洞的综合文献综述：研究挑战和未来方向

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-10 DOI: 10.1016/j.comnet.2025.111678

Tatyana Stojnic, A.S.M. Kayes, Wenny Rahayu, Mohammad Jabed Morshed Chowdhury

{"title":"A comprehensive literature review of cyber threats and vulnerabilities in IoT-driven satellite networks: Research challenges and future directions","authors":"Tatyana Stojnic, A.S.M. Kayes, Wenny Rahayu, Mohammad Jabed Morshed Chowdhury","doi":"10.1016/j.comnet.2025.111678","DOIUrl":"10.1016/j.comnet.2025.111678","url":null,"abstract":"<div><div>Satellite communications play an increasingly important role in a number of different industries with the rise of the Internet of Things (IoT). IoT-driven satellite (‘IoT-Satellite’ in short) networks have a number of vulnerabilities that can make them targets of common cyber attacks such as jamming and spoofing. These attacks can potentially be highly disruptive to the services they support. This paper presents a comprehensive survey of cyber threats and vulnerabilities with a focus on application areas in IoT-Satellite networks. Cyber threats include spoofing, jamming, malware and denial-of-service (DoS) attacks. Vulnerabilities in IoT-Driven satellite include deficits in encryption, access control and vulnerabilities in commercial off-the-shelf (COTS) parts. Subsequently, proposed in-depth solutions are also discussed in this paper. Proposed solutions include zero-trust security, software-defined networking, dynamic and context-based access control, blockchain and artificial intelligence (AI) approaches. While there are limited surveys specifically addressing IoT-driven satellite networks, we identify relevant studies and compare them with our work. Based on these findings we describe open research issues and potential future areas of research. The study suggests that further research is needed to develop a security framework for IoT-driven satellite networks, addressing prevalent cyber attacks and mitigating strategies.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111678"},"PeriodicalIF":4.6,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049705","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

Enhancing network performance in structured geometric network topologies: strategies for quality-of-service optimisation 在结构化几何网络拓扑中增强网络性能：服务质量优化策略

IF 4.6 2区计算机科学

Computer Networks Pub Date : 2025-09-10 DOI: 10.1016/j.comnet.2025.111713

Haotian Rao, João Paulo Ponciano, Muhammad Ali Imran

{"title":"Enhancing network performance in structured geometric network topologies: strategies for quality-of-service optimisation","authors":"Haotian Rao, João Paulo Ponciano, Muhammad Ali Imran","doi":"10.1016/j.comnet.2025.111713","DOIUrl":"10.1016/j.comnet.2025.111713","url":null,"abstract":"<div><div>The topology of a computer network is the basis for building a high-capacity, low-congestion network infrastructure. At present, the research on computer network topologies rests mainly on typically unstructured networks such as mesh networks. Our initial research presented in [1] explored the potential of using structured geometric network infrastructure designs to improve network performance. In this paper, we take our study forward to evaluate the performance of structured geometric network infrastructure designs under three QoS disciplines, namely weighted fair queuing (WFQ), priority queuing (PQ) and modified weighted round robin (MWRR). In this paper, we simulate structured geometric and unstructured network structures using Riverbed Modeler 18.9 to evaluate network performance. The simulation results illustrate that the structured geometric network topologies have better results than the unstructured network in response time and network delay under a high-load configuration, and the QoS algorithm provides advantages for voice services by prioritising the transmission of vital services.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"272 ","pages":"Article 111713"},"PeriodicalIF":4.6,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106013","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