Digital Communications and Networks最新文献

{"title":"ACSarF: a DRL-based adaptive consortium blockchain sharding framework for supply chain finance","authors":"Shijing Hu ,&nbsp;Junxiong Lin ,&nbsp;Xin Du ,&nbsp;Wenbin Huang ,&nbsp;Zhihui Lu ,&nbsp;Qiang Duan ,&nbsp;Jie Wu","doi":"10.1016/j.dcan.2023.11.008","DOIUrl":"10.1016/j.dcan.2023.11.008","url":null,"abstract":"<div><div>Blockchain technologies have been used to facilitate Web 3.0 and FinTech applications. However, conventional blockchain technologies suffer from long transaction delays and low transaction success rates in some Web 3.0 and FinTech applications such as Supply Chain Finance (SCF). Blockchain sharding has been proposed to improve blockchain performance. However, the existing sharding methods either use a static sharding strategy, which lacks the adaptability for the dynamic SCF environment, or are designed for public chains, which are not applicable to consortium blockchain-based SCF. To address these issues, we propose an adaptive consortium blockchain sharding framework named ACSarF, which is based on the deep reinforcement learning algorithm. The proposed framework can improve consortium blockchain sharding to effectively reduce transaction delay and adaptively adjust the sharding and blockout strategies to increase the transaction success rate in a dynamic SCF environment. Furthermore, we propose to use a consistent hash algorithm in the ACSarF framework to ensure transaction load balancing in the adaptive sharding system to further improve the performance of blockchain sharding in dynamic SCF scenarios. To evaluate the proposed framework, we conducted extensive experiments in a typical SCF scenario. The obtained experimental results show that the ACSarF framework achieves a more than 60% improvement in user experience compared to other state-of-the-art blockchain systems.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 1","pages":"Pages 26-34"},"PeriodicalIF":7.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138991534","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":"Block-gram: Mining knowledgeable features for efficiently smart contract vulnerability detection","authors":"Xueshuo Xie ,&nbsp;Haolong Wang ,&nbsp;Zhaolong Jian ,&nbsp;Yaozheng Fang ,&nbsp;Zichun Wang ,&nbsp;Tao Li","doi":"10.1016/j.dcan.2023.07.009","DOIUrl":"10.1016/j.dcan.2023.07.009","url":null,"abstract":"<div><div>Smart contracts are widely used on the blockchain to implement complex transactions, such as decentralized applications on Ethereum. Effective vulnerability detection of large-scale smart contracts is critical, as attacks on smart contracts often cause huge economic losses. Since it is difficult to repair and update smart contracts, it is necessary to find the vulnerabilities before they are deployed. However, code analysis, which requires traversal paths, and learning methods, which require many features to be trained, are too time-consuming to detect large-scale on-chain contracts. Learning-based methods will obtain detection models from a feature space compared to code analysis methods such as symbol execution. But the existing features lack the interpretability of the detection results and training model, even worse, the large-scale feature space also affects the efficiency of detection. This paper focuses on improving the detection efficiency by reducing the dimension of the features, combined with expert knowledge. In this paper, a feature extraction model <em>Block-gram</em> is proposed to form low-dimensional knowledge-based features from bytecode. First, the metadata is separated and the runtime code is converted into a sequence of opcodes, which are divided into segments based on some instructions (<em>jumps</em>, etc.). Then, scalable <em>Block-gram</em> features, including 4-dimensional block features and 8-dimensional attribute features, are mined for the learning-based model training. Finally, feature contributions are calculated from <em>SHAP</em> values to measure the relationship between our features and the results of the detection model. In addition, six types of vulnerability labels are made on a dataset containing <span><math><mn>33</mn><mo>,</mo><mn>885</mn></math></span> contracts, and these knowledge-based features are evaluated using seven state-of-the-art learning algorithms, which show that the average detection latency speeds up 25× to 650×, compared with the features extracted by <em>N-gram</em>, and also can enhance the interpretability of the detection model.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 1","pages":"Pages 1-12"},"PeriodicalIF":7.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44408705","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 teacher-student based attention network for fine-grained image recognition","authors":"Ang Li ,&nbsp;Xueyi Zhang ,&nbsp;Peilin Li ,&nbsp;Bin Kang","doi":"10.1016/j.dcan.2023.02.004","DOIUrl":"10.1016/j.dcan.2023.02.004","url":null,"abstract":"<div><div>Fine-grained Image Recognition (FGIR) task is dedicated to distinguishing similar sub-categories that belong to the same super-category, such as bird species and car types. In order to highlight visual differences, existing FGIR works often follow two steps: discriminative sub-region localization and local feature representation. However, these works pay less attention on global context information. They neglect a fact that the subtle visual difference in challenging scenarios can be highlighted through exploiting the spatial relationship among different sub-regions from a global view point. Therefore, in this paper, we consider both global and local information for FGIR, and propose a collaborative teacher-student strategy to reinforce and unity the two types of information. Our framework is implemented mainly by convolutional neural network, referred to Teacher-<strong>S</strong>tudent Based Attention Convolutional Neural Network (T-S-ACNN). For fine-grained local information, we choose the classic Multi-Attention Network (MA-Net) as our baseline, and propose a type of boundary constraint to further reduce background noises in the local attention maps. In this way, the discriminative sub-regions tend to appear in the area occupied by fine-grained objects, leading to more accurate sub-region localization. For fine-grained global information, we design a graph convolution based Global Attention Network (GA-Net), which can combine extracted local attention maps from MA-Net with non-local techniques to explore spatial relationship among sub-regions. At last, we develop a collaborative teacher-student strategy to adaptively determine the attended roles and optimization modes, so as to enhance the cooperative reinforcement of MA-Net and GA-Net. Extensive experiments on CUB-200-2011, Stanford Cars and FGVC Aircraft datasets illustrate the promising performance of our framework.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 1","pages":"Pages 52-59"},"PeriodicalIF":7.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44446560","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":"Security analysis and secured access design for networks of image remote sensing","authors":"Juan Zhao ,&nbsp;Haibo Dai ,&nbsp;Xiaolong Xu ,&nbsp;Hao Yan ,&nbsp;Zheng Zhang ,&nbsp;Chunguo Li","doi":"10.1016/j.dcan.2023.05.004","DOIUrl":"10.1016/j.dcan.2023.05.004","url":null,"abstract":"<div><div>The secured access is studied in this paper for the network of the image remote sensing. Each sensor in this network encounters the information security when uploading information of the images wirelessly from the sensor to the central collection point. In order to enhance the sensing quality for the remote uploading, the passive reflection surface technique is employed. If one eavesdropper that exists nearby this sensor is keeping on accessing the same networks, he may receive the same image from this sensor. Our goal in this paper is to improve the SNR of legitimate collection unit while cut down the SNR of the eavesdropper as much as possible by adaptively adjust the uploading power from this sensor to enhance the security of the remote sensing images. In order to achieve this goal, the secured energy efficiency performance is theoretically analyzed with respect to the number of the passive reflection elements by calculating the instantaneous performance over the channel fading coefficients. Based on this theoretical result, the secured access is formulated as a mathematical optimization problem by adjusting the sensor uploading power as the unknown variables with the objective of the energy efficiency maximization while satisfying any required maximum data rate of the eavesdropper sensor. Finally, the analytical expression is theoretically derived for the optimum uploading power. Numerical simulations verify the design approach.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 1","pages":"Pages 136-144"},"PeriodicalIF":7.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47541309","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":"In-band full-duplex MIMO PLC systems for relaying networks","authors":"Francisco J. Cañete ,&nbsp;Gautham Prasad ,&nbsp;Lutz Lampe","doi":"10.1016/j.dcan.2023.05.005","DOIUrl":"10.1016/j.dcan.2023.05.005","url":null,"abstract":"<div><div>In Power Line Communications (PLC), there are regulatory masks that restrict the transmit power spectral density for electromagnetic compatibility reasons, which creates coverage issues despite the not too long distances. Hence, PLC networks often employ repeaters/relays, especially in smart grid neighborhood area networks. Even in broadband indoor PLC systems that offer a notable data rate, relaying may pave the way to new applications like being the backbone for wireless technologies in a cost-effective manner to support the Internet-of-things paradigm. In this paper, we study Multiple-Input Multiple-Output (MIMO) PLC systems that incorporate in-band full-duplex functionality in relaying networks. We present several MIMO configurations that allow end-to-end half-duplex or full-duplex operations and analyze the achievable performance with state-of-the-art PLC systems. To reach this analysis, we get channel realizations from random network layouts for indoor and outdoor scenarios. We adopt realistic MIMO channel and noise models and consider transmission techniques according to PLC standards. The concepts discussed in this work can be useful in the design of future PLC relay-aided networks for different applications that look for a coverage extension and/or throughput: smart grids with enhanced communications in outdoor scenarios, and “last meter” systems for high-speed connections everywhere in indoor ones.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 1","pages":"Pages 145-159"},"PeriodicalIF":7.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42743222","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":"Communication delay-aware cooperative adaptive cruise control with dynamic network topologies—A convergence of communication and control","authors":"Jihong Liu ,&nbsp;Yiqing Zhou ,&nbsp;Ling Liu","doi":"10.1016/j.dcan.2023.07.004","DOIUrl":"10.1016/j.dcan.2023.07.004","url":null,"abstract":"<div><div>Wireless communication-enabled Cooperative Adaptive Cruise Control (CACC) is expected to improve the safety and traffic capacity of vehicle platoons. Existing CACC considers a conventional communication delay with fixed Vehicular Communication Network (VCN) topologies. However, when the network is under attack, the communication delay may be much higher, and the stability of the system may not be guaranteed. This paper proposes a novel communication Delay Aware CACC with Dynamic Network Topologies (DADNT). The main idea is that for various communication delays, in order to maximize the traffic capacity while guaranteeing stability and minimizing the following error, the CACC should dynamically adjust the VCN network topology to achieve the minimum inter-vehicle spacing. To this end, a multi-objective optimization problem is formulated, and a 3-step Divide-And-Conquer sub-optimal solution (3DAC) is proposed. Simulation results show that with 3DAC, the proposed DADNT with CACC can reduce the inter-vehicle spacing by 5%, 10%, and 14%, respectively, compared with the traditional CACC with fixed one-vehicle, two-vehicle, and three-vehicle look-ahead network topologies, thereby improving the traffic efficiency.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 1","pages":"Pages 191-199"},"PeriodicalIF":7.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45931588","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":"Latency minimization for multiuser computation offloading in fog-radio access networks","authors":"Wei Zhang ,&nbsp;Shafei Wang ,&nbsp;Ye Pan ,&nbsp;Qiang Li ,&nbsp;Jingran Lin ,&nbsp;Xiaoxiao Wu","doi":"10.1016/j.dcan.2023.05.011","DOIUrl":"10.1016/j.dcan.2023.05.011","url":null,"abstract":"<div><div>Recently, the Fog-Radio Access Network (F-RAN) has gained considerable attention, because of its flexible architecture that allows rapid response to user requirements. In this paper, computational offloading in F-RAN is considered, where multiple User Equipments (UEs) offload their computational tasks to the F-RAN through fog nodes. Each UE can select one of the fog nodes to offload its task, and each fog node may serve multiple UEs. The tasks are computed by the fog nodes or further offloaded to the cloud via a capacity-limited fronhaul link. In order to compute all UEs' tasks quickly, joint optimization of UE-Fog association, radio and computation resources of F-RAN is proposed to minimize the maximum latency of all UEs. This min-max problem is formulated as a Mixed Integer Nonlinear Program (MINP). To tackle it, first, MINP is reformulated as a continuous optimization problem, and then the Majorization Minimization (MM) method is used to find a solution. The MM approach that we develop is unconventional in that each MM subproblem is solved inexactly with the same provable convergence guarantee as the exact MM, thereby reducing the complexity of MM iteration. In addition, a cooperative offloading model is considered, where the fog nodes compress-and-forward their received signals to the cloud. Under this model, a similar min-max latency optimization problem is formulated and tackled by the inexact MM. Simulation results show that the proposed algorithms outperform some offloading strategies, and that the cooperative offloading can exploit transmission diversity better than noncooperative offloading to achieve better latency performance.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 1","pages":"Pages 160-171"},"PeriodicalIF":7.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86429946","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 multi-dimensional trust attestation solution in 5G-IoT","authors":"Xiangrong Li ,&nbsp;Yu Zhang ,&nbsp;Haotian Zhu ,&nbsp;Yubo Wang ,&nbsp;Junjia Huang","doi":"10.1016/j.dcan.2023.10.003","DOIUrl":"10.1016/j.dcan.2023.10.003","url":null,"abstract":"<div><div>The core missions of IoT are to sense data, transmit data and give feedback to the real world based on the calculation of the sensed data. The trust of sensing source data and transmission network is extremely important to IoT security. 5G-IoT with its low latency, wide connectivity and high-speed transmission extends the business scenarios of IoT, yet it also brings new challenges to trust proof solutions of IoT. Currently, there is a lack of efficient and reliable trust proof solutions for massive dynamically connected nodes, while the existing solutions have high computational complexity and can't adapt to time-sensitive services in 5G-IoT scenarios. In order to solve the above problems, this paper proposes an adaptive multi-dimensional trust proof solution. Firstly, the static and dynamic attributes of sensing nodes are metricized, and the historical interaction as well as the recommendation information are combined with the comprehensive metric of sensing nodes, and a multi-dimensional fine-grained trusted metric model is established in this paper. Then, based on the comprehensive metrics, the sensing nodes are logically grouped and assigned with service levels to achieve the screening and isolation of malicious nodes. At the same time, the proposed solution reduces the energy consumption of the metric process and optimizes the impact of real-time metrics on the interaction latency. Simulation experiments show that the solution can accurately and efficiently identify malicious nodes and effectively guarantee the safe and trustworthy operation of 5G-IoT nodes, while having a small impact on the latency of the 5G network.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 1","pages":"Pages 225-233"},"PeriodicalIF":7.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135707125","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":"Preamble slice orderly queue access scheme in cell-free dense communication systems","authors":"Jun Sun ,&nbsp;Mengzhu Guo ,&nbsp;Jian Liu","doi":"10.1016/j.dcan.2023.05.003","DOIUrl":"10.1016/j.dcan.2023.05.003","url":null,"abstract":"<div><div>High reliability applications in dense access scenarios have become one of the main goals of 6G environments. To solve the access collision of dense Machine Type Communication (MTC) devices in cell-free communication systems, an intelligent cooperative secure access scheme based on multi-agent reinforcement learning and federated learning is proposed, that is, the Preamble Slice Orderly Queue Access (PSOQA) scheme. In this scheme, the preamble arrangement is combined with the access control. The preamble arrangement is realized by preamble slices which is from the virtual preamble pool. The access devices learn to queue orderly by deep reinforcement learning. The orderly queue weakens the random and avoids collision. A preamble slice is assigned to an orderly access queue at each access time. The orderly queue is determined by interaction information among multiple agents. With the federated reinforcement learning framework, the PSOQA scheme is implemented to guarantee the privacy and security of agents. Finally, the access performance of PSOQA is compared with other random contention schemes in different load scenarios. Simulation results show that PSOQA can not only improve the access success rate but also guarantee low-latency tolerant performances.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 1","pages":"Pages 126-135"},"PeriodicalIF":7.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46378124","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 hierarchical blockchain-enabled distributed federated learning system with model contribution based rewarding","authors":"Haibo Wang ,&nbsp;Hongwei Gao ,&nbsp;Teng Ma ,&nbsp;Chong Li ,&nbsp;Tao Jing","doi":"10.1016/j.dcan.2024.07.002","DOIUrl":"10.1016/j.dcan.2024.07.002","url":null,"abstract":"<div><div>Distributed Federated Learning (DFL) technology enables participants to cooperatively train a shared model while preserving the privacy of their local datasets, making it a desirable solution for decentralized and privacy-preserving Web3 scenarios. However, DFL faces incentive and security challenges in the decentralized framework. To address these issues, this paper presents a Hierarchical Blockchain-enabled DFL (HBDFL) system, which provides a generic solution framework for the DFL-related applications. The proposed system consists of four major components, including a model contribution-based reward mechanism, a Proof of Elapsed Time and Accuracy (PoETA) consensus algorithm, a Distributed Reputation-based Verification Mechanism (DRTM) and an Accuracy-Dependent Throughput Management (ADTM) mechanism. The model contribution-based rewarding mechanism incentivizes network nodes to train models with their local datasets, while the PoETA consensus algorithm optimizes the tradeoff between the shared model accuracy and system throughput. The DRTM improves the system efficiency in consensus, and the ADTM mechanism guarantees that the throughput performance remains within a predefined range while improving the shared model accuracy. The performance of the proposed HBDFL system is evaluated by numerical simulations, with the results showing that the system improves the accuracy of the shared model while maintaining high throughput and ensuring security.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 1","pages":"Pages 35-42"},"PeriodicalIF":7.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141716872","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}