Digital Communications and Networks最新文献

{"title":"A generalized framework for downlink coverage analysis in polar-orbit LEO satellite","authors":"Sihoon Kwak,&nbsp;Inhoo Park,&nbsp;Moonsik Min","doi":"10.1016/j.dcan.2026.09.004","DOIUrl":"10.1016/j.dcan.2026.09.004","url":null,"abstract":"<div><div>Recent advancements in stochastic geometry have enabled tractable performance analysis of Low Earth Orbit (LEO) satellite constellations by modeling satellite locations as random point processes. These approaches offer valuable insights into average coverage behavior in large-scale networks. However, most prior studies impose restrictive assumptions such as fixed user locations at the poles or homogeneous satellite distributions, thereby limiting their applicability to realistic orbital configurations. In particular, for systems such as OneWeb, where multiple polar orbits intersect at the North Pole, the impact of user latitude becomes non-negligible and necessitates a more generalized modeling approach. This paper presents an analytical framework that captures the effect of arbitrary user locations on the coverage performance of polar-intersecting multi-orbit LEO satellite networks. Leveraging a OneWeb-inspired orbital structure, we derive a closed-form expression for the visible satellite trajectory length as a function of user latitude. This expression is then used to evaluate the coverage probability under an opportunistic communication scheme that selects the best visible satellite based on instantaneous geometry. Our analysis reveals that the visible satellite trajectory length increases with user latitude, which in turn improves the likelihood of finding a viable communication link. Moreover, we demonstrate that orbit selection diversity consistently enhances coverage probability across all latitudes, even under spatial randomness. These findings provide a more flexible and location-aware analytical basis for the design and optimization of next-generation LEO networks using stochastic geometry techniques.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 10","pages":"Pages 1529-1538"},"PeriodicalIF":6.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149352986","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":"Protocol state machine-based vulnerability discovery in 5G core control plane: an automated fuzzing approach","authors":"Xuanrui Xiong,&nbsp;Jinfeng Mao,&nbsp;Ling Yi,&nbsp;Xin Wan,&nbsp;Zhaolong Ning","doi":"10.1016/j.dcan.2026.10.004","DOIUrl":"10.1016/j.dcan.2026.10.004","url":null,"abstract":"<div><div>To meet the security vulnerability discovery demands of 5G control planes, we develop an automated fuzzing framework integrating Protocol State Machines (PSMs) with security attribute orchestration. First, we construct a PSM using natural language processing techniques. It employs a bidirectionally masked attention method and span attention encoding for semantic parsing of protocol specifications, followed by two-stage syntactic analysis using a Conditional Random Field (CRF) to extract state machine components. Automated generation can be subsequently realized through rule-based dictionary matching. Next, we design a PSM-guided fuzz testing method, which generates violation test templates by leveraging the state transition logic of PSM and integrating security attributes. Syntax-aware mutation combined with dynamic programming generates test cases, while a feedback-driven scheduling strategy is designed to optimize execution efficiency dynamically. Finally, experimental results demonstrate that the approach significantly improves the quality of test cases, enhances vulnerability discovery efficiency, and reduces testing costs.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 10","pages":"Pages 1549-1562"},"PeriodicalIF":6.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149352985","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":"Superdirective antenna arrays-aided wireless communications: a tutorial and review of recent advances","authors":"Haifan Yin,&nbsp;Mengying Gao,&nbsp;Liangcheng Han,&nbsp;Li Wei,&nbsp;Chongwen Huang","doi":"10.1016/j.dcan.2026.07.003","DOIUrl":"10.1016/j.dcan.2026.07.003","url":null,"abstract":"<div><div>Superdirective antenna arrays, characterized by their ability to achieve extremely high directivity in compact antenna arrays, hold significant promise for advancing wireless communications. This review provides a comprehensive overview of the theoretical foundations, practical considerations, and recent advances in superdirective antenna array-aided wireless communications. We begin with a review of classical superdirectivity theory. We then discuss the challenges that hinder the practical use of superdirective antenna arrays. Specifically, mutual coupling, high sensitivity, narrow bandwidth, poor radiation efficiency and hardware limitations are discussed, and recent efforts to address them are systematically reviewed. Emerging applications, such as multi-user communications, superdirective antenna pairs, and superdirective holographic array design and Electromagnetic Hybrid Beamforming (EHB) are also discussed. In addition, superdirective antenna array prototypes are surveyed. Finally, the potential research directions are also discussed for future development, including impedance matching, antenna design, integrated performance optimization, hardware implementation, and cross-layer system integration. This work aims to bridge the gap between theoretical developments and practical applications, serving as a valuable reference for both researchers and engineers in the field.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 10","pages":"Pages 1515-1528"},"PeriodicalIF":6.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149308676","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":"Hierarchical optimization based multi-objective dynamic regulation scheme for VANET topology","authors":"Ruixing Ren,&nbsp;Minqi Tao,&nbsp;Junhui Zhao,&nbsp;Xiaoke Sun,&nbsp;Qiuping Li","doi":"10.1016/j.dcan.2026.09.006","DOIUrl":"10.1016/j.dcan.2026.09.006","url":null,"abstract":"<div><div>As a core technology of intelligent transportation systems, vehicular ad-hoc networks support latency-sensitive services such as safety warning and cooperative perception via vehicle-to-everything communications. However, their highly dynamic topology increases average path length, raises latency, and reduces throughput, severely limiting communication performance. Existing topology optimization methods are deficient in multi-objective coordination, dynamic adaptation, and global-local synergy. To address these deficiencies, this paper proposes a two-layer dynamic topology regulation scheme that combines local feature aggregation with global adjustment. The scheme constructs a dynamic multi-objective optimization model integrating average path length and end-to-end latency, and achieves multi-index coordination via link adaptability metrics and a dynamic normalization mechanism. It rapidly responds to local link changes via feature fusion that integrates local node feature extraction with dynamic neighborhood sensing, and balances optimization accuracy and real-time performance using a dual-mode adaptive solving strategy for global topology adjustment. It reduces network oscillation risks by introducing a performance improvement threshold and a topology validity verification mechanism. Simulation results on real urban road networks using the SUMO platform demonstrate that the proposed scheme outperforms traditional methods in average path length (stabilizing at approximately 4 hops), end-to-end latency (maintained at around 0.01 s), and network throughput.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 10","pages":"Pages 1539-1548"},"PeriodicalIF":6.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149353105","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":"TAR-PZKP: a secure transmission scheme for vehicle accident reports using PUF and zero-knowledge proof","authors":"Lizhe Liu,&nbsp;Weijie Tan,&nbsp;Shangyu Lv,&nbsp;Huan Zhuang,&nbsp;Yuling Chen,&nbsp;Chunguo Li","doi":"10.1016/j.dcan.2026.06.005","DOIUrl":"10.1016/j.dcan.2026.06.005","url":null,"abstract":"<div><div>In the Internet of Vehicles (IoV), the large-scale deployment of smart vehicles has triggered new road traffic safety challenges. Particularly, existing vehicle accident report transmission schemes still face challenges such as privacy leakage, Single Point of Failure (SPOF), physical cloning attacks, and excessive computational overhead. To address these issues, this paper proposes a secure accident report transmission scheme that uses Non-Interactive Zero-Knowledge Proof (NIZKP) and Physically Unclonable Functions (PUF). This paper designs a decentralized authentication scheme for vehicle registration that prevents SPOF and privacy leakage. We also use the PUF to realize two-factor authentication login, which effectively resists physical cloning attacks. In addition, the authentication process uses NIZKP based on the Pedersen commitment to realize authentication for accident report coordination. At the end of the accident report coordination, it is passed into the blockchain for storage, realizing the secure transmission of accident reports. To reduce the storage as well as computation overhead, this paper uses a key derivation function to update the key. Finally, formal security analysis was conducted using the Real or Random (ROR) model and the ProVerif tool, the results prove that the proposed protocol meets security requirements. Comparing our proposed scheme with related schemes, the computational overhead of our V2V scheme is reduced by 42.4%, with higher security and lower communication overhead.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 9","pages":"Pages 1367-1383"},"PeriodicalIF":6.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145280","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":"Securing healthcare IoT: a meta-synthesis of challenges, solutions, and technology convergence","authors":"Mahmoud Zahedian Nezhad,&nbsp;Ali Javan Jafari Bojnordi,&nbsp;Seyed Amin Hosseini Seno,&nbsp;Javad Rezazadeh","doi":"10.1016/j.dcan.2026.07.004","DOIUrl":"10.1016/j.dcan.2026.07.004","url":null,"abstract":"<div><div>The Internet of Things (IoT) has transformed the healthcare industry, with technologies such as big data, blockchain, and artificial intelligence driving significant benefits through technology convergence. However, Healthcare IoT (H-IoT) systems face persistent security and privacy challenges. This meta-synthesis analyzes the current literature to identify key aspects of H-IoT security, including requirements, threats, and proposed technical solutions, while emphasizing the role of technology convergence in addressing these issues. The reviewed studies are categorized into two groups: qualitative research (focused on security features, requirements, threats, and attacks) and quantitative research (organized into six technical solution domains: blockchain; cryptography; authentication schemes and protocols; artificial intelligence and machine learning; H-IoT systems with embedded security solutions; and security and privacy frameworks). Finally, future research directions are explored to emphasize the critical role of technology convergence in enhancing H-IoT security.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 9","pages":"Pages 1396-1414"},"PeriodicalIF":6.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149203283","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":"A generalizable BERT-GNN hybrid framework for unified log anomaly detection","authors":"Caihong Wang,&nbsp;Du Xu,&nbsp;Yongsheng Zhao","doi":"10.1016/j.dcan.2026.04.001","DOIUrl":"10.1016/j.dcan.2026.04.001","url":null,"abstract":"<div><div>Logs are essential for monitoring large-scale distributed systems, yet their volume and structural heterogeneity pose substantial challenges for automated analysis. Conventional approaches often struggle to jointly model semantic information and temporal dependencies, which limits feature generalization across diverse environments. We propose Log2graphs, a generalizable framework for unified, unsupervised log analysis. Its core component, the Multi-Graph Autoencoder (MGAE), integrates Bidirectional Encoder Representations from Transformers (BERT) with a Graph Neural Network (GNN). Within MGAE, BERT extracts contextual semantic embeddings from raw log messages, while the GNN captures the chronological and topological correlations among log events. By reconstructing complex multi-graph structures, MGAE transforms sequential dependencies into low-dimensional representations without relying on labeled data. Experiments on widely used benchmark datasets, such as HDFS and BGL, show that the features extracted by MGAE improve downstream anomaly detection performance, outperforming baselines including LogFiT and LogFormer with F1 score gains of up to 11%. To extend benchmark validation to real-world settings with limited labeled datasets (e.g., HPC, Proxifier, and Zookeeper), we introduce a rigorous evaluation strategy using three domain-adaptive, label-free clustering metrics: Silhouette Score, Davies-Bouldin Index, and Calinski-Harabasz Index. This strategy enables quantitative assessment of the learned feature space in unsupervised environments and reduces reliance on ground-truth logs.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 9","pages":"Pages 1355-1366"},"PeriodicalIF":6.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145281","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":"Beyond theory: a comprehensive survey of clustering algorithm applications in wireless and media communications","authors":"Chen Wang,&nbsp;Yu Li,&nbsp;Ning Xie","doi":"10.1016/j.dcan.2026.06.004","DOIUrl":"10.1016/j.dcan.2026.06.004","url":null,"abstract":"<div><div>The burgeoning advancement in communication technologies, coupled with the widespread adoption of mobile devices, has led to an exponential increase in communication data volumes. Navigating this deluge of data in the big data era poses significant challenges in terms of processing and analysis. Clustering, an unsupervised learning approach, stands out as a potent analytical tool in this context, capable of segmenting data into groups of similar entities to unearth underlying patterns and structures. Given its capacity to discern intrinsic data relationships, clustering has garnered considerable interest for its potential applications within the communication field. Despite the wealth of research, many existing surveys either focus solely on the theoretical aspects of clustering algorithms or restrict their scope to a single domain, often overlooking the intrinsic synergy between data transmission and content processing. Addressing this gap, this survey delivers an exhaustive review of clustering algorithm applications from a unique cross-disciplinary perspective, bridging the realms of wireless communications and media communications. We argue that as communication systems evolve towards semantic and content-aware networking, a unified view of these domains is essential. This comprehensive review not only aids readers in grasping the varied applications of clustering algorithms—ranging from physical layer security to semantic image analysis—but also empowers researchers to refine algorithm design by drawing on analogous use cases across these sectors. To enhance comprehension, we elucidate diverse clustering algorithm implementations within wireless and media communications, illustrating with detailed examples. Moreover, we highlight prevailing challenges and delineate future research trajectories for clustering algorithm applications in these fields.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 9","pages":"Pages 1325-1354"},"PeriodicalIF":6.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149071896","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":"Information and communications technologies for carbon sinks from economics and engineering perspectives","authors":"Yuze Dong,&nbsp;Jinsong Wu","doi":"10.1016/j.dcan.2026.02.007","DOIUrl":"10.1016/j.dcan.2026.02.007","url":null,"abstract":"<div><div>Climate change has intensified the urgency of effective carbon sink solutions, yet the integration of Information and Communications Technologies (ICT) in these systems remains fragmented despite its transformative potential. This paper provides a comprehensive analysis of ICT applications in carbon sink projects from both economic and engineering perspectives, a dual lens approach rarely explored in the existing literature. In carbon trading, blockchain has improved transaction speed by 40%, while AI-based optimizations have reduced operational costs by 15% in projects such as Petra Nova. Through systematic examination, we identify three key findings: (1) ICT transforms carbon economics through digital financing platforms and blockchain-based trading systems, with AI enhancing price prediction, though data interoperability remains challenging; (2) digital technologies advance both natural and artificial sequestration from forest monitoring to Carbon Capture, Use and Storage (CCUS) optimization, yet lack integrated real-time control solutions; (3) realizing ICT’s full potential requires addressing its environmental costs, strengthening policy support, and fostering interdisciplinary collaboration. By bridging the economic engineering divide and mapping current applications alongside future opportunities, this paper demonstrates that deeper integration of digital technologies is essential to scale carbon sink solutions to meet climate targets.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 9","pages":"Pages 1501-1513"},"PeriodicalIF":6.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149254459","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":"Anomaly detection in industrial control networks based on deep reinforcement learning and data reconstruction","authors":"Hanjun Gao,&nbsp;Jiaqi Sun,&nbsp;Wei Feng,&nbsp;Xiaoxuan Fan,&nbsp;Wei Xiang,&nbsp;Shenghao Liu,&nbsp;Xianjun Deng","doi":"10.1016/j.dcan.2026.07.010","DOIUrl":"10.1016/j.dcan.2026.07.010","url":null,"abstract":"<div><div>Any anomaly in the data flow of industrial control networks can directly translate into security vulnerabilities within the control system. Therefore, maintaining continuous situational awareness of industrial control networks and achieving precise identification and effective handling of abnormal data are critical to ensuring the reliability and functional safety of control systems. Anomaly detection tasks in industrial control networks aim to identify behavior deviating from normal patterns within network traffic or device data. Although existing unsupervised and self-supervised learning methods can train models without labeled data, their performance is limited by prior assumptions about data distributions, and it is difficult to ensure model stability when the training data is contaminated. To this end, this paper designs a Data Reconstruction and Anomaly Detection method, termed as DRAD. Specifically, the proposed method reconstructs the original data from the perspective of complete data-sample features, rather than relying solely on partial attribute learning. DRAD comprises four core modules. The state representation module maps industrial data stream samples to states of a Markov decision process. The action generation module outputs reconstructed data via a deterministic policy network. The state sampling module uniformly samples interactions from the simulated environment within the training set. The reward computation module designs instantaneous rewards based on reconstruction errors. Each module collaboratively optimizes within a deep deterministic policy gradient framework to maximize long-term cumulative rewards and learn normal data patterns. Moreover, DRAD gradually converges to a more robust detection strategy through long-term exploration, thereby significantly enhancing the stability of detection performance. Extensive experiments on eight datasets show that DRAD improves the AUC-ROC and AUC-PR by 6.8%-17.0% and 12.1%-47.3% and improves robustness under different anomaly contamination rates compared with seven representative competing methods.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 9","pages":"Pages 1461-1469"},"PeriodicalIF":6.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149203286","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}