Computer Networks最新文献

{"title":"SD-MDN-TM: A traceback and mitigation integrated mechanism against DDoS attacks with IP spoofing","authors":"Suyue Wang ,&nbsp;Hua Wu ,&nbsp;Guang Cheng ,&nbsp;Xiaoyan Hu ,&nbsp;Jing Ren","doi":"10.1016/j.comnet.2024.110793","DOIUrl":"10.1016/j.comnet.2024.110793","url":null,"abstract":"<div><p>Traceback has been very attractive against DDoS attacks with IP spoofing instead of traditional mitigation methods because attacks require removal near attackers, resulting in affecting legitimate traffic as little as possible. There have been some approaches dedicated to achieving effective traceback. However, existing approaches often modify protocols to apply to multi-domain scenarios, and the implemented mitigation usually lags behind traceback. Therefore, this paper proposes the Software-Defined Multi-Domain Network Tracer and Mitigator (SD-MDN-TM) to traceback and mitigate DDoS attacks with IP spoofing in multi-domain SDN scenarios. We apply systematic sampling and flow feature extraction based on the Count-Min Sketch data structure for the lightweight statistics collection of massive DDoS attack traffic. We also design the TracebackTree data structure to construct the traceback paths of attackers of distributed attack sources. The Border Switch Trigger Mechanism is proposed to overcome the drawbacks of the commonly-used packet marking in cross-domain traceback information transfer, achieving no modification of existing network protocols and independent traceback among multiple domains. Mitigation is integrated with traceback for faster removal of attacks from the network. The proposed scheme can traceback DDoS attack sources both inside and outside domains accurately and effectively by constructing traceback path. It can be implemented without modifying the existing protocols, therefore achieving direct application to the existing network architecture. Furthermore, the traceback of attack sources outside domains can maintain independence in multi-domain scenarios. Mitigation integrated with traceback can achieve less impact on legitimate traffic and faster removal of attacks from the network.</p></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"254 ","pages":"Article 110793"},"PeriodicalIF":4.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274081","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":"NDN multicast over wireless networks: A survey on fundamentals, challenges, and open issues","authors":"André Luiz R. Madureira ,&nbsp;Leobino N. Sampaio","doi":"10.1016/j.comnet.2024.110815","DOIUrl":"10.1016/j.comnet.2024.110815","url":null,"abstract":"<div><div>Wireless devices have shown remarkable growth in data demand in the last decade due to the proliferation of smart devices and the emergence of bandwidth-hungry applications. This increasing data traffic demand is overcrowding the radio frequency spectrum, leading wireless multicast schemes to become a popular research topic again, as they provide efficient data dissemination. NDN supports multicast communication by design. It is a networked system formed by named entities that adopt a communication model focusing on the content rather than its location. The architecture follows a receiver-driven communication model through which content consumers retrieve data through semantically meaningful names instead of specific destinations. Its properties are essential for multicast communication on ad hoc networks, as its features provide enhanced support for dynamic topologies, decentralized control, and the self-organization of participant nodes that communicate without needing a pre-existing network infrastructure. However, despite the wireless medium being broadcast by nature, NDN multicast is still challenging in wireless scenarios, especially in ad hoc environments, due to the node’s high mobility, link instability, constant handovers, and data transmission over a shared medium. Hence, this survey discusses the benefits of NDN for mobile scenarios through an in-depth analysis of NDN multicast features, focusing on fundamentals, challenges, and open issues when applied to wireless networking.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"254 ","pages":"Article 110815"},"PeriodicalIF":4.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142315330","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":"An efficient beam sweeping scheme with backup paging occasions in NR-Unlicensed Spectrum","authors":"Eshita Rastogi ,&nbsp;Abhishek Roy ,&nbsp;Ayush Rastogi ,&nbsp;Jaehoon (Paul) Jeong ,&nbsp;Navrati Saxena","doi":"10.1016/j.comnet.2024.110811","DOIUrl":"10.1016/j.comnet.2024.110811","url":null,"abstract":"<div><div>With the increasing demand of user applications and the shortage of cellular spectrum, New Radio (NR) access to Unlicensed Spectrum (NR-U) is getting significant attention. Listen Before Talk (LBT) procedure is used to sense unlicensed channel availability prior to transmission. The transmissions are subjected to LBT procedure failure, which brings extra delay as they are postponed to the next available transmission opportunity. This excess delay also affects time-critical procedures, such as paging. The directional communication in NR requires beamforming, which further complicates paging procedure as additional paging message transmissions are needed to cover all the beams. In this work, we propose an NR-U paging mechanism (called <span><math><mrow><mi>F</mi><mi>F</mi><mtext>_</mtext><mi>B</mi><mi>P</mi></mrow></math></span>) consisting of Full and Fast Paging Cycles with Backup Paging Occasions (POs). Full Paging uses a normal NR-U paging cycle and broadcasts a paging message on all the beams. On the other hand, Fast Paging, which targets delay-sensitive mobile users, uses a shorter paging cycle and broadcasts a paging message on selected beams only. The Backup POs deal with LBT procedure failure impairments while paging broadcast on selective beams reduces paging resource usage. We analyze <span><math><mrow><mi>F</mi><mi>F</mi><mtext>_</mtext><mi>B</mi><mi>P</mi></mrow></math></span> using a discrete-time semi-Markov chain model and validate the model by extensive simulations. The simulation results show that <span><math><mrow><mi>F</mi><mi>F</mi><mtext>_</mtext><mi>B</mi><mi>P</mi></mrow></math></span> outperforms several baseline mechanisms in terms of average paging delay and paging resource usage.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"254 ","pages":"Article 110811"},"PeriodicalIF":4.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319860","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":"Leveraging tabular GANs for malicious address classification in ethereum network","authors":"Muhammad Ahtazaz Ahsan,&nbsp;Amna Arshad,&nbsp;Adnan Noor Mian","doi":"10.1016/j.comnet.2024.110813","DOIUrl":"10.1016/j.comnet.2024.110813","url":null,"abstract":"<div><div>The popularity of ethereum for cryptocurrency transactions attracts malicious actors to engage in illegal activities like phishing, ponzi, and gambling. Previous studies have focused mainly on phishing due to the large number of phishing addresses. However, there is no work done on ponzi or gambling classification due to the limited availability of these addresses, which makes their classification more challenging. In this paper, we propose a machine learning (ML) based method for classifying malicious addresses in ethereum, with a specific focus on phishing, ponzi, and gambling addresses. We use a selective upsampling technique through the tabular generative adversarial network (GAN) to solve limited data problems. We perform not only binary but also multiclass classification on various feature extraction methods, including Trans2Vec and Node2Vec, using Ethereum transactional data. We evaluate our method on <span><math><msub><mrow><mi>F</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span> score, precision, recall, and accuracy. Our results show that the proposed method is effective in ponzi and gambling detection when compared with the state-of-the-art.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"254 ","pages":"Article 110813"},"PeriodicalIF":4.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419360","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":"Towards the future of bot detection: A comprehensive taxonomical review and challenges on Twitter/X","authors":"Danish Javed ,&nbsp;NZ Jhanjhi ,&nbsp;Navid Ali Khan ,&nbsp;Sayan Kumar Ray ,&nbsp;Alanoud Al Mazroa ,&nbsp;Farzeen Ashfaq ,&nbsp;Shampa Rani Das","doi":"10.1016/j.comnet.2024.110808","DOIUrl":"10.1016/j.comnet.2024.110808","url":null,"abstract":"<div><div>Harmful Twitter Bots (HTBs) are widespread and adaptable to a wide range of social network platforms. The use of social network bots on numerous social network platforms is increasing. As the popularity and utility of social networking bots grow, the attacks using social network-based automated accounts are getting more coordinated, resulting in crimes that might endanger democracy, the financial market, and public health. HTB designers develop their bots to elude detection while academics create several algorithms to identify social media bot accounts. This field is active and necessitates ongoing improvement due to the never-ending cat-and-mouse game. X, previously known as Twitter, is among the biggest social network platforms that has been plagued by automated accounts. Even though new research is being conducted to tackle this issue, the number of bots on Twitter keeps on increasing. In this research, we establish a robust theoretical foundation in the continuously evolving domain of Harmful Twitter Bot (HTB) detection by analyzing the existing HTB detection techniques. Our research provides an extensive literature review and introduces an enhanced taxonomy that has the potential to help the scientific community form better generalizations for HTB detection. Furthermore, we discuss this domain's obstacles and open challenges to direct and improve future research. As far as we are aware, this study marks the first comprehensive examination of HTB detection that includes articles published between June 2013 and August 2023. The review's findings include a more thorough classification of detection approaches, a spotlight on ways to spot Twitter bots, and a comparison of recent HTB detection methods. Moreover, we provide a comprehensive list of publicly available datasets for HTB detection. As bots evolve, efforts must be made to raise awareness, equip legitimate users with information, and help future researchers in the field of social network bot detection.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"254 ","pages":"Article 110808"},"PeriodicalIF":4.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142327851","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":"A two-step linear programming approach for repeater placement in large-scale quantum networks","authors":"Romtham Sripotchanart ,&nbsp;Weisheng Si ,&nbsp;Rodrigo N. Calheiros ,&nbsp;Qing Cao ,&nbsp;Tie Qiu","doi":"10.1016/j.comnet.2024.110795","DOIUrl":"10.1016/j.comnet.2024.110795","url":null,"abstract":"<div><p>Thanks to the applications such as Quantum Key Distribution and Distributed Quantum Computing, the deployment of quantum networks is gaining great momentum. A major component in quantum networks is repeaters, which are essential for reducing the error rate of qubit transmission for long-distance links. However, repeaters are expensive devices, so minimizing the number of repeaters placed in a quantum network while satisfying performance requirements becomes an important problem. Existing solutions typically solve this problem optimally by formulating an Integer Linear Program (ILP). However, the number of variables in their ILPs is <span><math><mrow><mi>O</mi><mrow><mo>(</mo><msup><mrow><mi>n</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>)</mo></mrow></mrow></math></span>, where <span><math><mi>n</mi></math></span> is the number of nodes in a network. This incurs infeasible running time when the network scale is large. To overcome this drawback, this paper proposes to solve the repeater placement problem by two steps, with each step using a linear program of a much smaller scale with <span><math><mrow><mi>O</mi><mrow><mo>(</mo><mi>n</mi><mo>)</mo></mrow></mrow></math></span> variables. Although this solution is not optimal, it dramatically reduces the time complexity, making it practical for large-scale networks. Moreover, it constructs networks that have higher node connectivity than those by existing solutions, since it deploys slightly more number of repeaters into networks. Our extensive experiments on both synthetic and real-world network topologies verified our claims.</p></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"254 ","pages":"Article 110795"},"PeriodicalIF":4.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1389128624006273/pdfft?md5=514277d17e6855a7161cf9235a13a0a6&pid=1-s2.0-S1389128624006273-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274083","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":"Network traffic prediction based on PSO-LightGBM-TM","authors":"Feng Li ,&nbsp;Wei Nie ,&nbsp;Kwok-Yan Lam ,&nbsp;Li Wang","doi":"10.1016/j.comnet.2024.110810","DOIUrl":"10.1016/j.comnet.2024.110810","url":null,"abstract":"<div><p>Network traffic prediction is critical in wireless network management by allowing a good estimate of the traffic trend, which is also an important approach for detecting traffic anomalies in order to enhance network security. Deep-learning-based method has been widely adopted to predict network traffic matrix (TM) though with the main drawbacks in high complexity and low efficiency. In this paper, we propose a traffic prediction model based on Particle Swarm Optimization (PSO) and LightGBM (PSO-LightGBM-TM), which optimizes the LightGBM parameters for each network flow by PSO so that LightGBM can adapt to each of the network traffic flow. Compared with existing commonly used deep learning models, our model has a more straightforward structure and yet outperforms existing deep learning models. Sufficient comparison tests on three real network traffic datasets, Abilene, GÉANT, and CERNET have been conducted, and the results show that our model provides more accurate results and higher prediction efficiency.</p></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"254 ","pages":"Article 110810"},"PeriodicalIF":4.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274077","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":"GCP: A multi-strategy improved wireless sensor network model for environmental monitoring","authors":"Jun Wang ,&nbsp;Ning Wang ,&nbsp;Haoju Wang ,&nbsp;Kerang Cao ,&nbsp;Ahmed M. El-Sherbeeny","doi":"10.1016/j.comnet.2024.110807","DOIUrl":"10.1016/j.comnet.2024.110807","url":null,"abstract":"<div><p>Nowadays, smart environmental monitoring devices are widely used in various fields, and one of the most representative tools is the wireless sensor network (WSN). WSNs are easy to deploy and provide real-time information feedback, which is very suitable for environmental monitoring. As we all know, the environmental monitoring network because of the special nature of its work requirements, the need for uninterrupted and real-time transmission of monitoring data, which leads to energy consumption is extremely large, and this cannot meet the needs of its long-term work. Existing traditional routing has problems such as unscientific cluster head election and high redundancy in data transmission, which usually lead to a large amount of energy consumption, which is not conducive to the long-term stable operation of sensor networks. In this paper, we improve the traditional routing protocol and design a cluster head election method based on the genetic algorithm, which proposes a new fitness function in terms of energy, distance, and the number of nodes in the cluster, and performs the selection of cluster head nodes based on this method. In addition, we propose a new grey prediction model, which can realize the real-time update of data queues, and optimize the data transmission process of traditional WSNs based on this prediction model to reduce the amount of intra-cluster data transmission. Combining these improvements, a grey cluster prediction (GCP) model is proposed, and the performance of the model is tested based on real mine and soil data sets. The simulation results show that the model significantly reduces energy loss and extends the network life cycle while ensuring the integrity of data transmission. It can also meet the requirements of long-term stable operation of environmental monitoring equipment.</p></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"254 ","pages":"Article 110807"},"PeriodicalIF":4.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274078","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":"A truthful double auction mechanism for resource provisioning and elastic service in vehicle computing","authors":"Xi Liu ,&nbsp;Jun Liu ,&nbsp;Weidong Li","doi":"10.1016/j.comnet.2024.110806","DOIUrl":"10.1016/j.comnet.2024.110806","url":null,"abstract":"<div><p>Intelligent vehicles, equipped with powerful computing and sensing resources, serve as versatile mobile computing platforms, offering many resources to users. This study focuses on resource provisioning and elastic service to address the paramount issue of resource provisioning for in-vehicle computing. It introduces an elastic sensing service, enabling users to declare multiple requested areas to obtain sensing data. It allows various vehicles to collaborate in providing services to a single user when individual vehicles cannot complete the task alone. The approach formulated as a double auction-based setting involves a market with multiple self-interested users and vehicles. The main objective is to design a mechanism that maximizes social welfare. First, a greedy mechanism provides different task allocation strategies while ensuring truthfulness. The proposed mechanism is truthful and equilibrium-driven, achieving individual rationality, consumer sovereignty, and budget balance. It demonstrates the approximation ratio. Simulation results indicate that the proposed mechanism can increase social welfare and the number of served users by at least 29% and 9%, respectively, compared with baseline methods. This research paves the way for more efficient resource provisioning in intelligent vehicles, ultimately enhancing these mobile computing platforms’ overall user experience and capabilities.</p></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"254 ","pages":"Article 110806"},"PeriodicalIF":4.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-objective joint optimization of task offloading based on MADRL in internet of things assisted by satellite networks","authors":"Houpeng Wang ,&nbsp;Suzhi Cao ,&nbsp;Huanjing Li ,&nbsp;Lei Yan ,&nbsp;Zhonglin Guo ,&nbsp;Yu’e Gao","doi":"10.1016/j.comnet.2024.110801","DOIUrl":"10.1016/j.comnet.2024.110801","url":null,"abstract":"<div><div>The Internet of Things (IoT) integrates a large number of heterogeneous terminals and systems, possessing ubiquitous sensing and computing capabilities. Satellite networks are the crucial supplement to terrestrial networks, particularly in remote areas where network infrastructures are sparingly distributed or unavailable. Combining edge computing with satellite networks provides on-orbit computing capabilities for IoT applications, reducing service delay and enhancing service quality. Due to the resource constraints of satellites, achieving collaborative services through task offloading among multiple satellites becomes essential. Both the privacy leakage risk arising from frequent data interactions and the load imbalance resulting from offloading preferences cannot be overlooked. The key challenge of task offloading is to safeguard the privacy of offloaded data and ensure the system’s load balance while minimizing the delay and energy consumption. In this paper, the task offloading problem is formulated as a Partially Observable Markov Decision Process (POMDP), and a task offloading algorithm based on multi-objective joint optimization using multi-agent deep reinforcement learning in a distributed architecture is proposed. The simulation results validate the efficacy of our model and algorithm, demonstrating that our proposed algorithm achieves better performance in minimizing comprehensive offloading costs.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"254 ","pages":"Article 110801"},"PeriodicalIF":4.4,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1389128624006339/pdfft?md5=db265398ca7ed57c38d747a29dd0706e&pid=1-s2.0-S1389128624006339-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312482","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}