International Journal of Network Management最新文献

{"title":"Network Security Threats and Defense Mechanisms for 6G Multi-Virtual Network Scenarios","authors":"Yu Zhou","doi":"10.1002/nem.70003","DOIUrl":"https://doi.org/10.1002/nem.70003","url":null,"abstract":"<div>\u0000 \u0000 <p>The introduction of 6G networks presents substantial challenges for network security, particularly in multi-virtual network topologies. The combination of network function virtualization (NFV) and software-defined networking (SDN) in 6G is designed to increase scalability and flexibility; nevertheless, these advances complicate network security management. The goal is to identify risks to network security and develop defense solutions for 6G multi-virtual network situations. SDN's virtualized network functions (VNFs) are utilized to provide stateful firewall services that provide scalable and dynamic threat prevention. The SDN controller is critical in developing a set of rules to prevent risky network connectivity and decrease possible risks. 6G multi-virtual network domains—attacking threats that involve different socket addresses so complex that usually applicable protection measures hardly tackle that scenario, machine learning (ML) algorithms, and Intelligent Osprey Optimized Versatile Random Forest (IOO-VRF) model—have been proposed for potentially harmful connection detection and predicting cyber threats accessing the network. Multiple open-access sources can be exploited to gather diverse data for collecting valuable information on studying network traffic and cyber threats. The experimental results indicate that IOO-VRF achieved prediction accuracy comparable to that of other traditional algorithms. The proposed model is assessed on various types of metrics, including accuracy (98%), precision (97.4%), recall (94%), and F1-score (93%). The results emphasized the importance of ML in combination with SDN and NFV for security in the case of resilient, expandable, and flexible security measures for future multi-virtual 6G network communications networks.</p>\u0000 </div>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"35 2","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Innovative Application of 6G Network Slicing Driven by Artificial Intelligence in the Internet of Vehicles","authors":"Xueqin Ni,&nbsp;Zhiyuan Dong,&nbsp;Xia Rong","doi":"10.1002/nem.70004","DOIUrl":"https://doi.org/10.1002/nem.70004","url":null,"abstract":"<div>\u0000 \u0000 <p>The rapid growth of vehicle networks in the Internet of Vehicles (IoV) needs novel approaches to optimizing network resource allocation and enhancing traffic management. Sixth-generation (6G) network slicing, when paired with artificial intelligence (AI), has enormous potential in this field. The purpose of this research is to investigate the use of AI-driven 6G network slicing (NS) for efficient usage of resources and accurate traffic prediction in IoV systems. A unique network design is suggested, combining data-driven approaches and dynamic network slicing. Data are acquired from vehicular sensors and traffic monitoring systems, and log transformation is used to handle exponential growth patterns like vehicle counts and congestion levels. The Fourier transform (FT) is used to extract frequency-domain information from traffic data, which allows for the detection of periodic patterns, trends, and anomalies such as vehicle velocity and traffic density. The Dipper Throated Optimized Efficient Elman Neural Network (DTO-EENN) is used to forecast traffic and optimize resources. This technology allows the system to predict traffic patterns and dynamically alter network slices to ensure optimal resource allocation while reducing latency. The results show that the suggested AI-driven NS technique increases forecast accuracy and network performance while dramatically reducing congestion levels. The research indicates that AI-driven 6G based NS offers a solid framework for optimizing IoV performance.</p>\u0000 </div>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"35 2","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"SDOG: Scalable Scheduling of Flows Based on Dynamic Online Grouping in Industrial Time-Sensitive Networks","authors":"Chang Liu,&nbsp;Jin Wang,&nbsp;Chang Liu Sr,&nbsp;Jie Wang,&nbsp;Li Tian,&nbsp;Xiao Yu,&nbsp;Min Wei","doi":"10.1002/nem.70001","DOIUrl":"https://doi.org/10.1002/nem.70001","url":null,"abstract":"<div>\u0000 \u0000 <p>Although many studies have conducted the traffic scheduling of time-sensitive networks, most focus on small-scale static scheduling for specific scenarios, which cannot cope with dynamic and rapid scheduling of time-triggered (TT) flows generated in scalable scenarios in the Industrial Internet of Things. In this paper, we propose a Scalable TT flow scheduling method based on Dynamic Online Grouping in industrial time-sensitive networks (SDOG). To achieve that, we establish an undirected weighted flow graph based on the conflict index between TT flows and divide available time into equally spaced time windows. We dynamically group the TT flows within each window locally. When the number of flows to be scheduled doubles, we can achieve scalable and efficient solutions to efficiently schedule dynamic TT flows, avoiding unnecessary conflicts during data communication. In addition, a topology pruning strategy is adopted to prune the network topology of each group, reducing unnecessary link variables and further effectively shortening the scheduling time. Experimental results validated our expected performance and demonstrated that our proposed SDOG scheduling method has advantages in terms of overall traffic schedulability and average time for scheduling individual traffic.</p>\u0000 </div>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"35 2","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Mitigating BGP Route Leaks With Attributes and Communities: A Stopgap Solution for Path Plausibility","authors":"Nils Höger,&nbsp;Nils Rodday,&nbsp;Gabi Dreo Rodosek","doi":"10.1002/nem.70002","DOIUrl":"https://doi.org/10.1002/nem.70002","url":null,"abstract":"<p>The Border Gateway Protocol (BGP) is known to have serious security vulnerabilities. One of these vulnerabilities is BGP route leaks. A BGP route leak describes the propagation of route announcements beyond their intended scope, violating the Gao-Rexford model. Route leaks may lead to traffic misdirection, causing performance issues and potential security risks, often due to mistakes and misconfiguration. Several potential solutions have been published and are currently greatly discussed within the Internet Engineering Task Force (IETF) but have yet to be widely implemented. One approach is the Autonomous System Provider Authorization (ASPA). In addition to these new approaches, there are also efforts to use existing BGP functionalities to detect and prevent route leaks. In this paper, we implement the Down Only (DO) Community and Only to Customer (OTC) Attribute approaches, using them isolated and in conjunction with ASPA. Our research indicates that implementing a DO/OTC deployment strategy focusing on well-interconnected ASes could significantly reduce route leaks. Specifically, we observed mitigation of over 98% of all route leaks when DO and OTC were deployed by the top 5% of the most connected ASes. We show that combining DO/OTC and ASPA can greatly enhance ASPA's route leak prevention capabilities.</p>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"35 2","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/nem.70002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Positional Packet Capture for Anomaly Detection in Multitenant Virtual Networks","authors":"Daniel Spiekermann","doi":"10.1002/nem.2326","DOIUrl":"https://doi.org/10.1002/nem.2326","url":null,"abstract":"<p>Anomaly detection in multitenant virtual networks presents significant challenges due to the dynamic, ephemeral nature of virtualized environments and the complex traffic patterns they generate. This paper presents a definition of preferable positions within virtual networks to enhance anomaly detection efficacy. Leveraging a combination of overlay and underlay capture positions, this paper examines the strategic impact of network positioning on anomaly detection accuracy, particularly in environments utilizing software-defined networking (SDN) and network function virtualization (NFV). Through controlled testing with realistic attack scenarios, including data exfiltration, denial of service, and malware infiltration, the advantages and constraints of each capture position are demonstrated. The findings underscore the necessity of adaptable capture mechanisms to address variability in data volume, encapsulation challenges, and privacy concerns unique to virtualized ecosystems. The paper further introduces a cost calculation model that evaluates each capture position by weighting key factors, enabling an optimized trade-off between detection accuracy and resource efficiency. The derived classification of the positional value significantly improves real-time detection of both internal and external threats within multitenant networks.</p>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"35 2","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/nem.2326","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Buy Crypto, Sell Privacy: An Extended Investigation of the Cryptocurrency Exchange Evonax","authors":"Alexander Brechlin,&nbsp;Jochen Schäfer,&nbsp;Frederik Armknecht","doi":"10.1002/nem.2325","DOIUrl":"https://doi.org/10.1002/nem.2325","url":null,"abstract":"<p>Cryptocurrency exchanges have become a multi-billion dollar industry. Although these platforms are not only relevant for economic reasons but also from a privacy and legal perspective, empirical studies investigating the operations of cryptocurrency exchanges and the behavior of their users are surprisingly rare. A notable exception is a study analyzing the cryptocurrency exchange <i>ShapeShift</i>. While this study described new heuristics to retrieve a significant fraction of trades made on the plaform, its approach relied on identifying cryptocurrency transactions based on previously scraped trade data. This limited the analysis to the timeframe for which data had been acquired and likely led to false negatives in the transaction identification process. In this paper, we replicate and extend previous work by conducting an in-depth investigation of the cryptocurrency exchange <i>Evonax</i>. Our analysis is based on actual trading data acquired by using a novel methodology allowing to extract detailed information from the public blockchain and the interface of the exchange platform. We are able to identify 30,402 transactions between the launch of Evonax in February 2018 and December 31, 2022, which should be close to a complete set of all transactions. This allows us not only to analyze the business practices of a cryptocurrency exchange but also to identify a number of interesting use cases that are likely to be associated with illegal activity. This paper is an extended version of a research article previously accepted at the CryptoEx Workshop at IEEE ICBC 2024.</p>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"35 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/nem.2325","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143119279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Music Transmission and Performance Optimization Based on the Integration of Artificial Intelligence and 6G Network Slice","authors":"Honghui Zhu","doi":"10.1002/nem.70000","DOIUrl":"https://doi.org/10.1002/nem.70000","url":null,"abstract":"<div>\u0000 \u0000 <p>Network slicing, which enables efficient resource management to meet specific service requirements, provides a scalable solution for optimizing music transmission and live performance in mobile networks beyond 5G and into 6G. The research focuses on optimizing live performances as well as music transmission. Since AI-driven resource management improves performance quality and real-time music streaming in dynamic 6G network situations, these factors are interconnected. This approach allows multiple tenants, such as event organizers and music producers, to share infrastructure while customizing communication and quality standards for real-time music services. To ensure optimal resource allocation, including high bandwidth, low latency, and consistent service quality, network slices are dynamically configured by the infrastructure provider. Although the implementation of network slicing in the core network has been well studied, applying it within the radio access network (RAN) presents challenges, especially given the unpredictability of wireless channels and the strict quality of service (QoS) demands for live music streaming. For 6G networks, the article suggests a tenant-driven RAN slicing method improved by artificial intelligence (AI) to maximize music performance and transmission. A hybrid AI framework integrates a deep recurrent neural network (DRNN) for continuous monitoring and prediction of network conditions with a deep Q-network (DQN) augmented by prioritized experience replay (PER) for real-time resource adaptation. The DRNN forecasts network states to guide high-level resource allocation, whereas DQN with PER dynamically manages routing and bandwidth based on past critical network states, enabling rapid responses to fluctuating performance demands. Comparative results indicate that the suggested approach outperforms conventional techniques, achieving a latency of 25 ms, an audio quality of 4.6, and a bandwidth utilization of 90%. Simulation results in live music and enhanced mobile broadband (eMBB) environments demonstrate the proposed approach's effectiveness in minimizing latency, enhancing audio quality, and stabilizing transmission, surpassing traditional network allocation techniques.</p>\u0000 </div>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"35 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143117930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 New English Education Model Based on 6G and Sliced Network Virtual Reality Platform","authors":"Xiaozheng Liu","doi":"10.1002/nem.2324","DOIUrl":"https://doi.org/10.1002/nem.2324","url":null,"abstract":"<div>\u0000 \u0000 <p>The information society has led to a shift in traditional English education methods, with the evolution of technology, particularly internet and communication network technologies, reshaping the teaching landscape. This facilitated innovative instructional approaches and enhanced the learning experience. This research introduces a novel virtual learn net architecture (VLNA) within the 6G network layers, which processes the performance of the virtual reality-based English education system (VR-EES) model to provide a seamless, personalized learning experience for online learners. This architecture is structured into several layers: The user equipment (UE) layer connects VR headsets to the network with ultrareliable, low-latency links; the radio access network (RAN) layer, employing massive MIMO and beam forming, enhances connection speed, capacity, and coverage. Edge computing handles latency-sensitive tasks like speech recognition and adaptive content delivery, reducing the load on the core network. The core network layer (CLN) manages network slices for specific learning tasks such as real-time interaction, high-definition multimedia, and computation-intensive processes, with control plane and user plane separation (CUPS) optimizing network management and security through end-to-end encryption. Software-defined networking (SDN) and network function virtualization (NFV) provide centralized, dynamic control, allowing real-time resource allocation based on demand. Cloud-edge integration supports Artificial intelligence (AI)-driven adaptive learning, optimizing educational content delivery based on individual progress. The study results demonstrate that stimulation of VLNA achieved significant improvements in latency reduction, bandwidth utilization, throughput, packet loss rate, jitter, user engagement, learning efficiency, and user satisfaction. The integration of edge computing and network slicing led to a significant reduction in latency, while the enhanced throughput enabled seamless VR experiences. In this study, latency reduction, bandwidth utilization, and user satisfaction emerge as the most significant factors, with user satisfaction standing out as the top performer due to its substantial impact on enhancing the overall learning experience. The packet loss rate is maintained to a certain level, ensuring reliable data transmission. The VR-EES model's experimental results also enhanced visual learning, multimedia quality, user pleasure, learning effectiveness, and user engagement.</p>\u0000 </div>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"35 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143114896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Log-TF-IDF and NETCONF-Based Network Switch Anomaly Detection","authors":"Sukhyun Nam,&nbsp;Eui-Dong Jeong,&nbsp;James Won-Ki Hong","doi":"10.1002/nem.2322","DOIUrl":"https://doi.org/10.1002/nem.2322","url":null,"abstract":"<div>\u0000 \u0000 <p>In this study, we propose and evaluate a model that utilizes both log data and state data to detect abnormal conditions in network switches. Building upon our previous research and drawing inspiration from TF-IDF used in natural language processing to measure word importance, we propose a statistical method, Log-TF-IDF, to quantify the rarity of each log pattern in the log data. Furthermore, based on this Log-TF-IDF, we introduce the AB Score, which quantifies how abnormal the current log pattern is. Our findings indicate that the AB Score is notably higher and more volatile in abnormal conditions. We confirm that anomaly detection is feasible through the AB Score, which has the advantage of being computationally efficient due to its statistical basis. We combined the metrics generated during the AB Score calculation with resource data collected with NETCONF and developed a machine-learning model to detect abnormal conditions in network switches. We confirm that this model can detect abnormal conditions with an F1 score of 0.86 on our collected dataset, confirming its viability for detecting abnormal states in network equipment.</p>\u0000 </div>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"35 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143114895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Multitopology Routing With Virtual Topologies and Segment Routing","authors":"Nicolas Huin,&nbsp;Sébastien Martin,&nbsp;Jérémie Leguay","doi":"10.1002/nem.2321","DOIUrl":"https://doi.org/10.1002/nem.2321","url":null,"abstract":"<div>\u0000 \u0000 <p>Multitopology routing (MTR) provides an attractive alternative to segment routing (SR) for traffic engineering when network devices cannot be upgraded. However, due to a high overhead in terms of link state messages exchanged by topologies and the need to frequently update link weights to follow evolving network conditions, MTR is often limited to a small number of topologies and the satisfaction of loose QoS constraints. To overcome these limitations, we propose virtual MTR (vMTR), an MTR extension where demands are routed over virtual topologies that are silent; that is, they do not exchange LSA messages and that are continuously derived from a very limited set of real topologies, optimizing each QoS parameter. In this context, we present a polynomial and exact algorithm for vMTR and, as a benchmark, a local search algorithm for MTR. We show that vMTR helps to reduce drastically the number of real topologies and that it is more robust to QoS changes. In the case where SR can actually be rolled-out, we also show that vMTR allows to drastically reduce SR overhead.</p>\u0000 </div>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"35 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143114966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}