Computer Communications最新文献_第7页

QUICL: Disruption-tolerant networking via a QUIC convergence layer QUIC：通过QUIC汇聚层的容错网络

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-06-27 DOI: 10.1016/j.comcom.2025.108247

Markus Sommer, Artur Sterz, Markus Vogelbacher, Hicham Bellafkir, Bernd Freisleben

{"title":"QUICL: Disruption-tolerant networking via a QUIC convergence layer","authors":"Markus Sommer, Artur Sterz, Markus Vogelbacher, Hicham Bellafkir, Bernd Freisleben","doi":"10.1016/j.comcom.2025.108247","DOIUrl":"10.1016/j.comcom.2025.108247","url":null,"abstract":"<div><div>Disruption-tolerant networks (DTNs) have a wide range of applications, including emergencies where traditional communication infrastructure has been destroyed, remote rural deployments where communication infrastructure does not exist, and environmental monitoring in which animals are equipped with sensors and transmit data whenever they come into contact with a base station. Using the de-facto DTN protocol standard, Bundle Protocol version 7, nodes transmit data using Convergence Layer Protocols, which serve as abstractions for the underlying communication technology. In this article, we introduce <em>QUICL</em>, a novel convergence layer for disruption-tolerant networks. QUICL is built on the QUIC transport protocol, which offers advantages over TCP in a disruption-tolerant setting. In particular, it improves congestion control, supports multiplexing, ensures reliable transmission, effectively manages unstable networks, and encrypts traffic by default. Our implementation, already merged upstream, is based on the free and open-source <em>DTN7-go</em>-protocol suite and the <em>QUIC-go</em>-library. Our experimental evaluation shows that even in challenging situations such as bundle transmission over 63 hops with a packet loss of 30% on each hop, <em>QUICL</em> still delivers data where most other DTN software/convergence layer combinations fail to transmit any data.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"241 ","pages":"Article 108247"},"PeriodicalIF":4.5,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144535407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

IoT-ONDDQN: A detection model based on deep reinforcement learning for IoT data security IoT- onddqn：基于深度强化学习的物联网数据安全检测模型

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-06-27 DOI: 10.1016/j.comcom.2025.108263

Yutao Hu , Yongxin Feng , Yuntao Zhao , Xuedong Mao

{"title":"IoT-ONDDQN: A detection model based on deep reinforcement learning for IoT data security","authors":"Yutao Hu , Yongxin Feng , Yuntao Zhao , Xuedong Mao","doi":"10.1016/j.comcom.2025.108263","DOIUrl":"10.1016/j.comcom.2025.108263","url":null,"abstract":"<div><div>Internet of Things (IoT) devices are frequently targeted by malicious traffic, leading to data leaks and even device malfunctions. The variety and rapid evolution of IoT malicious traffic attacks pose a significant challenge to existing intrusion detection systems (IDS). Therefore, this paper uses the CIC-IoT2023 malicious traffic dataset specifically designed for IoT devices and builds detection models for OneR Deep Q Network (IoT-ODQN) and OneR Noisynet Double DQN (IoT-ONDDQN) based on Deep Reinforcement Learning (DRL). They use the OneR classifier for feature engineering, providing well-performing feature inputs for model training, and utilizing the experience replay mechanism to reuse and train samples repeatedly. IoT-ONDDQN replaces the <em>ɛ</em>-greedy strategy with Noisynet for more dynamic learning. The performance of these two detection models is compared with several existing Machine Learning (ML) and Deep Learning (DL) models. Experimental results show that IoT-ODQN and IoT-ONDDQN outperform the comparison models in terms of loss values, accuracy, precision, recall, and F1 score for the 8-classification and 34-classification tasks, DRL has better detection ability compared to ML and DL models. In addition, the improved IoT-ONDDQN outperforms the IoT-ODQN base model in all evaluation metrics and has better stability and robustness.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"241 ","pages":"Article 108263"},"PeriodicalIF":4.5,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144580995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Securing ICS networks: SDN-based Automated Traffic Control and MTD Defensive Framework against DDoS attacks ICS网络安全：基于sdn的自动流量控制和MTD防御框架，防御DDoS攻击

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-06-26 DOI: 10.1016/j.comcom.2025.108252

Xingsheng Qin , Robin Doss , Frank Jiang , Xingguo Qin , Biyue Long

引用次数: 0

Optimizing mobility prediction in 5G for enhanced C-V2X applications: A multidisciplinary research survey 优化5G的移动性预测以增强C-V2X应用：一项多学科研究调查

IF 4.3 3区计算机科学

Computer Communications Pub Date : 2025-06-25 DOI: 10.1016/j.comcom.2025.108254

Mario Bou Abboud , Maroua Drissi , Oumaya Baala , Sylvain Allio

{"title":"Optimizing mobility prediction in 5G for enhanced C-V2X applications: A multidisciplinary research survey","authors":"Mario Bou Abboud , Maroua Drissi , Oumaya Baala , Sylvain Allio","doi":"10.1016/j.comcom.2025.108254","DOIUrl":"10.1016/j.comcom.2025.108254","url":null,"abstract":"<div><div>With the advent of 5G New Radio technologies, autonomous vehicles are evolving from isolated units into components of a larger, interconnected system. This transformation is enabled by robust Vehicle-to-Everything (V2X) communications, facilitating applications such as high-definition sensor data sharing and collision avoidance within the Cellular-V2X (C-V2X) framework. Nationwide, ultra-reliable, low-latency coverage is crucial for these applications, necessitating a smart, flexible network to manage mobility uncertainties effectively. To achieve this, mobility prediction will play a pivotal role by preparing the network for anticipated traffic patterns and optimizing its radio and computational resources, thereby enhancing overall efficiency. This survey provides a comprehensive review and analysis of current and emerging mobility prediction methodologies essential for enhancing these networks. We explore these methodologies along with the standards and requirements set by key organizations like the 3rd Generation Partnership Project (3GPP) and industry leaders such as the 5G Automotive Association (5GAA). By reviewing state-of-the-art mobility prediction techniques, this survey critically analyzes their role in forecasting key network performance indicators (KPIs), enabling proactive resource allocation, robust edge-computing strategies, and slice orchestration, all crucial for optimizing 5G performance and ensuring ultra-reliable, low-latency C-V2X communications.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"242 ","pages":"Article 108254"},"PeriodicalIF":4.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Robustness of decentralised learning to nodes and data disruption 分散学习对节点和数据中断的鲁棒性

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-06-24 DOI: 10.1016/j.comcom.2025.108250

Luigi Palmieri , Chiara Boldrini , Lorenzo Valerio , Andrea Passarella , Marco Conti , János Kertész

{"title":"Robustness of decentralised learning to nodes and data disruption","authors":"Luigi Palmieri , Chiara Boldrini , Lorenzo Valerio , Andrea Passarella , Marco Conti , János Kertész","doi":"10.1016/j.comcom.2025.108250","DOIUrl":"10.1016/j.comcom.2025.108250","url":null,"abstract":"<div><div>In the active landscape of AI research, decentralised learning is gaining momentum. Decentralised learning allows individual nodes to keep data locally where they are generated and to share knowledge extracted from local data among themselves through an interactive process of collaborative refinement. This paradigm supports scenarios where data cannot leave the data owner node due to privacy or sovereignty reasons or real-time constraints imposing proximity of models to locations where inference has to be carried out. The distributed nature of decentralised learning implies significant new research challenges with respect to centralised learning. Among them, in this paper, we focus on robustness issues. Specifically, we study the effect of nodes’ disruption on the collective learning process. Assuming a given percentage of “central” nodes disappear from the network, we focus on different cases, characterised by (i) different distributions of data across nodes and (ii) different times when disruption occurs with respect to the start of the collaborative learning task. Through these configurations, we are able to show the non-trivial interplay between the properties of the network connecting nodes, the persistence of knowledge acquired collectively before disruption or lack thereof, and the effect of data availability pre- and post-disruption. Our results show that decentralised learning processes are remarkably robust to network disruption. As long as even minimum amounts of data remain available somewhere in the network, the learning process is able to recover from disruptions and achieve significant classification accuracy. This clearly varies depending on the remaining connectivity after disruption, but we show that even nodes that remain completely isolated can retain significant knowledge acquired before the disruption.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"241 ","pages":"Article 108250"},"PeriodicalIF":4.5,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144518344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Fuzzy logic-based IDS (FLIDS) for the detection of different types of jamming attacks in IoT networks 基于模糊逻辑的IDS （FLIDS）用于检测物联网网络中不同类型的干扰攻击

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-06-24 DOI: 10.1016/j.comcom.2025.108251

Michael Savva , Iacovos Ioannou , Vasos Vassiliou

{"title":"Fuzzy logic-based IDS (FLIDS) for the detection of different types of jamming attacks in IoT networks","authors":"Michael Savva , Iacovos Ioannou , Vasos Vassiliou","doi":"10.1016/j.comcom.2025.108251","DOIUrl":"10.1016/j.comcom.2025.108251","url":null,"abstract":"<div><div>Jamming attacks pose a critical threat to the security and reliability of Internet of Things (IoT) networks by disrupting communication and degrading network performance. Existing intrusion detection systems often struggle to provide real-time and adaptive defense mechanisms against sophisticated jamming techniques. This study introduces the Fuzzy Logic Intrusion Detection System (FLIDS), designed for efficient, real-time detection of jamming attacks in IoT environments. This work significantly extends previous research by providing a more comprehensive validation of FLIDS across a broader range of attack scenarios and system evaluations. FLIDS demonstrates high accuracy in identifying various jamming strategies, including constant, deceptive, random, reactive, and complex jammers, achieving detection rates of up to 97.51% for reactive jammers and 96.73% for deceptive jammers as detailed in this extended study. The system operates efficiently in resource-constrained IoT environments, enabling autonomous and distributed detection with minimal computational overhead. New analyses further explore its scalability and performance under dynamic conditions. Extensive simulations in Contiki OS and Cooja validate FLIDS’s effectiveness across diverse network topologies. These results establish FLIDS as a robust and practical solution for enhancing IoT security against jamming attacks.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"241 ","pages":"Article 108251"},"PeriodicalIF":4.5,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 Self-adaptive Hybrid Network Anomaly Detection Engine 一种自适应混合网络异常检测引擎

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-06-23 DOI: 10.1016/j.comcom.2025.108248

Amir Mohammadi Bagha , Isaac Woungang , Issa Traore , Danda B. Rawat

{"title":"A Self-adaptive Hybrid Network Anomaly Detection Engine","authors":"Amir Mohammadi Bagha , Isaac Woungang , Issa Traore , Danda B. Rawat","doi":"10.1016/j.comcom.2025.108248","DOIUrl":"10.1016/j.comcom.2025.108248","url":null,"abstract":"<div><div>Network anomaly detection faces new challenges with the rising complexity of enterprise networks and cyber threats. This paper presents a Self-adaptive Hybrid Network Anomaly Detection Engine (denoted SHADE), that operates over the Activity and Event Networks (AEN) graph model. SHADE stems from the combination three key modules: (1) a two-stage detection framework that combines unsupervised pattern mining with supervised classification, (2) a self-adaptive threshold mechanism that dynamically adjusts to network behavior changes, and (3) a transfer learning module that enables zero-day attack detection. The unsupervised stage uses an autoencoder with Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) to identify potential anomalies in AEN event sequences. The supervised stage employs an ensemble classifier to validate and categorize these anomalies. SHADE is evaluated using three widely-used public datasets: CICIDS2018, IoT-23, and UNSW-NB15, containing a combined total of <span><math><mrow><mn>1</mn><msup><mrow><mn>0</mn></mrow><mrow><mn>6</mn></mrow></msup></mrow></math></span> network events. Our results show that SHADE achieves 94.3% detection accuracy and 0.8% false positive rate. It is also demonstrated that SHADE achieves 87.2% accuracy in detecting previously unseen attacks.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"241 ","pages":"Article 108248"},"PeriodicalIF":4.5,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144513658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Flexible and efficient privacy-preserving fine-grained access control scheme for data sharing in cloud-edge collaborative IoT 灵活高效的保护隐私的细粒度访问控制方案，用于云边缘协同物联网数据共享

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-06-23 DOI: 10.1016/j.comcom.2025.108259

Sensen Li , Meigen Huang , Chen Fang , Bin Yu

{"title":"Flexible and efficient privacy-preserving fine-grained access control scheme for data sharing in cloud-edge collaborative IoT","authors":"Sensen Li , Meigen Huang , Chen Fang , Bin Yu","doi":"10.1016/j.comcom.2025.108259","DOIUrl":"10.1016/j.comcom.2025.108259","url":null,"abstract":"<div><div>—The cloud-edge collaborative Internet of Things (IoT) can provide a promising solution for real-time services. However, widespread concerns about the security of private data arise owing to the involvement of interest-oriented third parties. Although ciphertext-policy attribute-based encryption (CP-ABE) can achieve the fine-grained access control for outsourced data, existing schemes are unsuitable for cloud-edge collaborative IoT. Specifically, there are three main issues: <em>1)</em> access policies in the form of plaintext or semi-ciphertext may reveal the privacy; <em>2)</em> dynamically updating access policies for outsourced data is challenging, let alone in the state where the policies are fully hidden; and <em>3)</em> the massive complex operations involved impose an enormous burden on resource-constrained end devices. To address these challenges, we proposed a flexible and efficient privacy-preserving ABE (FE2P-ABE) scheme that enabled the flexible policy updating in the fully hidden policy state. FE2P-ABE supports the large attribute universe and expressive access structure, and is friendly to resource-constrained devices, which greatly alleviates the computational burden on end devices by integrating online/offline encryption and verifiable outsourced decryption. Additionally, FE2P-ABE was formally proven to be selectively indistinguishable against the chosen plaintext attack, and the theoretical analysis and experimental simulation confirmed its superior performance in terms of storage and computation overhead while achieving comprehensive functionality.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"241 ","pages":"Article 108259"},"PeriodicalIF":4.5,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144501627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Analysis and implementation of Discrete Time Markov Chain based method for pilot decontamination in cognitive radio based ultra-dense networks 基于离散时间马尔可夫链的认知无线电超密集网络导频去污方法分析与实现

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-06-20 DOI: 10.1016/j.comcom.2025.108246

Subrat Kumar Sethi, Arunanshu Mahapatro

{"title":"Analysis and implementation of Discrete Time Markov Chain based method for pilot decontamination in cognitive radio based ultra-dense networks","authors":"Subrat Kumar Sethi, Arunanshu Mahapatro","doi":"10.1016/j.comcom.2025.108246","DOIUrl":"10.1016/j.comcom.2025.108246","url":null,"abstract":"<div><div>In the context of beyond 5G (B5G) systems, the deployment of ultra-dense networks (UDNs) equipped with a large number of base-station antennas holds the promise of achieving high spectral efficiency (SE) through Cognitive Radio Network (CRN) technology. However, this approach introduce the issue of pilot contamination (PC), stemming from the reuse of pilots in adjacent cells, which has a detrimental impact on channel estimation and overall network performance. To address this issue comprehensively, we propose the SD-GraW-PD scheme for CRNs. Our scheme begins by categorizing users into two groups: cell-centered and cell-edged users. To further mitigate the effects of PC, we introduce a Discrete Time Markov Chain (DTMC)-based approach that leverages mutually orthogonal Graeco-Latin squares matrix pilot allocation. Additionally, we apply DTMC analysis to implement the Weighted Graph-Coloring Pilot Decontamination (WGC-PD) technique, enhancing the decontamination process, particularly for cell-edged users. Through extensive numerical simulations, we evaluate the proposed methodology. The results unequivocally demonstrate significant improvements in network performance, including enhancements in uplink achievable rate and SINR, in comparison to existing methods. Our DTMC-based approach emerges as an efficient and effective solution to the persistent PC problem within CR-based UDNs, offering promising prospects for achieving higher SE in the context of B5G systems.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"241 ","pages":"Article 108246"},"PeriodicalIF":4.5,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144366569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

UAV-assisted small base station ON-OFF switching in 6G cellular networks considering backhaul energy consumption 考虑回传能耗的6G蜂窝网络中无人机辅助小型基站开断切换

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-06-18 DOI: 10.1016/j.comcom.2025.108253

Samaneh Khadem Khorasani, Behrouz Shahgholi Ghahfarokhi, Naser Movahhedinia

{"title":"UAV-assisted small base station ON-OFF switching in 6G cellular networks considering backhaul energy consumption","authors":"Samaneh Khadem Khorasani, Behrouz Shahgholi Ghahfarokhi, Naser Movahhedinia","doi":"10.1016/j.comcom.2025.108253","DOIUrl":"10.1016/j.comcom.2025.108253","url":null,"abstract":"<div><div>The emergence of 6th Generation (6G) cellular networks presents an opportunity to redefine Key Performance Indicators (KPIs) necessary for high-quality communications in the 2030s. 6G aims to innovate through novel architectural designs and the utilization of higher frequency bands, alongside incorporating aerial coverage to establish a three-dimensional network framework in contrast to its predecessor, 5G. Central to this innovation are Unmanned Aerial Vehicles (UAVs), which can be used as Drone Base Stations (DBSs). Despite the energy required for UAVs to hover, they can significantly decrease energy consumption and environmental impact by replacing terrestrial cellular infrastructure and switching off underutilized or inefficient Small Base Stations (SBSs) in Ultra-Dense Networks (UDNs). This work presents an energy-efficient UAV-assisted On-Off switching methodology that considers energy usage of DBSs’ backhaul links, in contrast to previous studies. By optimizing DBS placement, user association, and power control, the approach aims to improve energy efficiency. The problem is formulated as a Mixed-Integer Nonlinear Programming (MINLP) optimization, which is then decomposed into three manageable sub-problems that are solved using proposed algorithms. This methodological framework not only alleviates the complexity associated with the original problem but also enables practical implementations in energy-constrained UAV systems, ultimately leading to improved energy efficiency compared to existing approaches. Simulation results demonstrate about 90 % improvement of energy efficiency compared to prior studies even when fewer SBSs are switched off. Furthermore, the proposed approach exhibits 95 % better energy efficiency rather than previous methods when the serving time of UAVs increases.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"241 ","pages":"Article 108253"},"PeriodicalIF":4.5,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144518475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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