Pub Date : 2026-01-01Epub Date: 2024-08-08DOI: 10.1016/j.dcan.2024.08.005
Hongjun Li , Debiao He , P. Vijayakumar , Fayez Alqahtani , Amr Tolba
Smart cities, as a typical application in the field of the Internet of Things, can combine cloud computing to realize the intelligent control of objects and process massive data. While cloud computing brings convenience to smart city services, a serious problem is ensuring that confidential data cannot be leaked to malicious adversaries. Considering the security and privacy of data, data owners transmit sensitive data in its encrypted form to cloud server, which seriously hinders the improvements of potential utilization and efficient sharing. Public key searchable encryption ensures that users can securely retrieve the encrypted data without decryption. However, most existing schemes cannot resist keyword guessing attacks or the size of trapdoors linearly increases with the number of data owners. In this work, by utilizing certificateless encryption and proxy re-encryption, we design an authenticated searchable encryption scheme with constant trapdoors. The designed scheme preserves the privacy of index ciphertexts and keyword trapdoors, and can resist keyword guessing attacks. In addition, data users can generate and upload trapdoors with lower computation and communication overheads. We show that the proposed scheme is suitable for smart city implementations and applications by experimentally evaluating its performance.
{"title":"A certificateless and KGA-secure searchable encryption scheme with constant trapdoors in smart city","authors":"Hongjun Li , Debiao He , P. Vijayakumar , Fayez Alqahtani , Amr Tolba","doi":"10.1016/j.dcan.2024.08.005","DOIUrl":"10.1016/j.dcan.2024.08.005","url":null,"abstract":"<div><div>Smart cities, as a typical application in the field of the Internet of Things, can combine cloud computing to realize the intelligent control of objects and process massive data. While cloud computing brings convenience to smart city services, a serious problem is ensuring that confidential data cannot be leaked to malicious adversaries. Considering the security and privacy of data, data owners transmit sensitive data in its encrypted form to cloud server, which seriously hinders the improvements of potential utilization and efficient sharing. Public key searchable encryption ensures that users can securely retrieve the encrypted data without decryption. However, most existing schemes cannot resist keyword guessing attacks or the size of trapdoors linearly increases with the number of data owners. In this work, by utilizing certificateless encryption and proxy re-encryption, we design an authenticated searchable encryption scheme with constant trapdoors. The designed scheme preserves the privacy of index ciphertexts and keyword trapdoors, and can resist keyword guessing attacks. In addition, data users can generate and upload trapdoors with lower computation and communication overheads. We show that the proposed scheme is suitable for smart city implementations and applications by experimentally evaluating its performance.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 1","pages":"Pages 198-209"},"PeriodicalIF":7.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146189434","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}
Pub Date : 2026-01-01Epub Date: 2025-01-30DOI: 10.1016/j.dcan.2025.01.004
Srinivasa Gowda G. K , Hayder M.A. Ghanimi , Sudhakar Sengan , Kolla Bhanu Prakash , Meshal Alharbi , Roobaea Alroobaea , Sultan Algarni , Abdullah M. Baqasah
Advanced technologies like Cyber-Physical Systems (CPS) and the Internet of Things (IoT) have supported modernizing and automating the transportation region through the introduction of Intelligent Transportation Systems (ITS). Integrating CPS-ITS and IoT provides real-time Vehicle-to-Infrastructure (V2I) communication, supporting better traffic management, safety, and efficiency. These technological innovations generate complex problems that need to be addressed, uniquely about data routing and Task Scheduling (TS) in ITS. Attempts to solve those problems were primarily based on traditional and experimental methods, and the solutions were not so successful due to the dynamic nature of ITS. This is where the scope of Machine learning (ML) and Swarm Intelligence (SI) has significantly impacted dealing with these challenges; in this line, this research paper presents a novel method for TS and data routing in the CPS-ITS. This paper proposes using a cutting-edge ML algorithm for data transmission from CPS-ITS. This ML has Gated Linear Unit-approximated Reinforcement Learning (GLRL). Greedy Iterative-Particle Swarm Optimization (GI-PSO) has been recommended to develop the Particle Swarm Optimization (PSO) for TS. The primary objective of this study is to enhance the security and effectiveness of ITS systems that utilize CPS-ITS. This study trained and validated the models using a network simulation dataset of 50 nodes from numerous ITS environments. The experiments demonstrate that the proposed GLRL reduces End-to-End Delay (EED) by 12%, enhances data size use from 83.6% to 88.6%, and achieves higher bandwidth allocation, particularly in high-demand scenarios such as multimedia data streams where adherence improved to 98.15%. Furthermore, the GLRL reduced Network Congestion (NC) by 5.5%, demonstrating its efficiency in managing complex traffic conditions across several environments. The model passed simulation tests in three different environments: urban (UE), suburban (SE), and rural (RE). It met the high bandwidth requirements, made task scheduling more efficient, and increased network throughput (NT). This proved that it was robust and flexible enough for scalable ITS applications. These innovations provide robust, scalable solutions for real-time traffic management, ultimately improving safety, reducing NC, and increasing overall NT. This study can affect ITS by developing it to be more responsive, safe, and effective and by creating a perfect method to set up UE, SE, and RE.
{"title":"Optimizing the cyber-physical intelligent transportation system network using enhanced models for data routing and task scheduling","authors":"Srinivasa Gowda G. K , Hayder M.A. Ghanimi , Sudhakar Sengan , Kolla Bhanu Prakash , Meshal Alharbi , Roobaea Alroobaea , Sultan Algarni , Abdullah M. Baqasah","doi":"10.1016/j.dcan.2025.01.004","DOIUrl":"10.1016/j.dcan.2025.01.004","url":null,"abstract":"<div><div>Advanced technologies like Cyber-Physical Systems (CPS) and the Internet of Things (IoT) have supported modernizing and automating the transportation region through the introduction of Intelligent Transportation Systems (ITS). Integrating CPS-ITS and IoT provides real-time Vehicle-to-Infrastructure (V2I) communication, supporting better traffic management, safety, and efficiency. These technological innovations generate complex problems that need to be addressed, uniquely about data routing and Task Scheduling (TS) in ITS. Attempts to solve those problems were primarily based on traditional and experimental methods, and the solutions were not so successful due to the dynamic nature of ITS. This is where the scope of Machine learning (ML) and Swarm Intelligence (SI) has significantly impacted dealing with these challenges; in this line, this research paper presents a novel method for TS and data routing in the CPS-ITS. This paper proposes using a cutting-edge ML algorithm for data transmission from CPS-ITS. This ML has Gated Linear Unit-approximated Reinforcement Learning (GLRL). Greedy Iterative-Particle Swarm Optimization (GI-PSO) has been recommended to develop the Particle Swarm Optimization (PSO) for TS. The primary objective of this study is to enhance the security and effectiveness of ITS systems that utilize CPS-ITS. This study trained and validated the models using a network simulation dataset of 50 nodes from numerous ITS environments. The experiments demonstrate that the proposed GLRL reduces End-to-End Delay (EED) by 12%, enhances data size use from 83.6% to 88.6%, and achieves higher bandwidth allocation, particularly in high-demand scenarios such as multimedia data streams where adherence improved to 98.15%. Furthermore, the GLRL reduced Network Congestion (NC) by 5.5%, demonstrating its efficiency in managing complex traffic conditions across several environments. The model passed simulation tests in three different environments: urban (UE), suburban (SE), and rural (RE). It met the high bandwidth requirements, made task scheduling more efficient, and increased network throughput (NT). This proved that it was robust and flexible enough for scalable ITS applications. These innovations provide robust, scalable solutions for real-time traffic management, ultimately improving safety, reducing NC, and increasing overall NT. This study can affect ITS by developing it to be more responsive, safe, and effective and by creating a perfect method to set up UE, SE, and RE.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 1","pages":"Pages 210-222"},"PeriodicalIF":7.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146189435","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}
Pub Date : 2026-01-01Epub Date: 2024-08-08DOI: 10.1016/j.dcan.2024.08.006
Zhenzhen Wang , Bing He , Zixin Jiang , Xianyang Zhang , Haidi Dong , Di Ye
Multi-Agent Systems (MAS), which consist of multiple interacting agents, are crucial in Cyber-Physical Systems (CPS), because they improve system adaptability, efficiency, and robustness through parallel processing and collaboration. However, most existing unsupervised meta-learning methods are centralized and not suitable for multi-agent systems where data are distributed stored and inaccessible to all agents. Meta-GMVAE, based on Variational Autoencoder (VAE) and set-level variational inference, represents a sophisticated unsupervised meta-learning model that improves generative performance by efficiently learning data representations across various tasks, increasing adaptability and reducing sample requirements. Inspired by these advancements, we propose a novel Distributed Unsupervised Meta-Learning (DUML) framework based on Meta-GMVAE and a fusion strategy. Furthermore, we present a DUML algorithm based on Gaussian Mixture Model (DUMLGMM), where the parameters of the Gaussian-mixture are solved by an Expectation-Maximization algorithm. Simulations on Omniglot and MiniImageNet datasets show that DUMLGMM can achieve the performance of the corresponding centralized algorithm and outperform non-cooperative algorithm.
{"title":"Distributed unsupervised meta-learning algorithm over multi-agent systems","authors":"Zhenzhen Wang , Bing He , Zixin Jiang , Xianyang Zhang , Haidi Dong , Di Ye","doi":"10.1016/j.dcan.2024.08.006","DOIUrl":"10.1016/j.dcan.2024.08.006","url":null,"abstract":"<div><div>Multi-Agent Systems (MAS), which consist of multiple interacting agents, are crucial in Cyber-Physical Systems (CPS), because they improve system adaptability, efficiency, and robustness through parallel processing and collaboration. However, most existing unsupervised meta-learning methods are centralized and not suitable for multi-agent systems where data are distributed stored and inaccessible to all agents. Meta-GMVAE, based on Variational Autoencoder (VAE) and set-level variational inference, represents a sophisticated unsupervised meta-learning model that improves generative performance by efficiently learning data representations across various tasks, increasing adaptability and reducing sample requirements. Inspired by these advancements, we propose a novel Distributed Unsupervised Meta-Learning (DUML) framework based on Meta-GMVAE and a fusion strategy. Furthermore, we present a DUML algorithm based on Gaussian Mixture Model (DUMLGMM), where the parameters of the Gaussian-mixture are solved by an Expectation-Maximization algorithm. Simulations on Omniglot and MiniImageNet datasets show that DUMLGMM can achieve the performance of the corresponding centralized algorithm and outperform non-cooperative algorithm.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 1","pages":"Pages 134-142"},"PeriodicalIF":7.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079616","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}
Pub Date : 2026-01-01Epub Date: 2025-04-18DOI: 10.1016/j.dcan.2025.04.002
Xingwei Wang , Haiquan Lu , Jieni Zhang , Yong Zeng
Delay Alignment Modulation (DAM) is an innovative broadband modulation technique well-suited for millimeter Wave (mmWave) and Terahertz (THz) massive Multiple-Input Multiple-Output (MIMO) communication systems. Leveraging the high spatial resolution and sparsity of multi-path channels, DAM effectively mitigates Inter-Symbol Interference (ISI) by aligning all multi-path components through a combination of delay pre-compensation (or post-compensation) and path-based beamforming. As such, ISI is eliminated while preserving multi-path power gains. In this paper, we investigate multi-user double-side DAM, which incorporates both delay pre-compensation at the transmitter and post-compensation at the receiver, in contrast to prior works that primarily focus on single-side DAM with only delay pre-compensation. Firstly, we derive the constraint on the number of introduced delays and formulate the corresponding delay pre/post-compensation vectors tailored for multi-user double-side DAM, given a specific number of delay compensations. Furthermore, we demonstrate that when the number of Base Stations (BSs)/User Equipment (UE) antennas is sufficiently large, single-side DAM—where delay compensation is performed only at the BS/UE—is preferable to double-side DAM, since the former results in less ISI to be spatially eliminated. Next, we propose two low-complexity path-based beamforming strategies based on the eigen-beamforming transmission and ISI-Zero Forcing (ZF), respectively. On this basis, we further analyze the achievable sum rates. Simulation results verify that with a sufficiently large number of BS/UE antennas, single-side DAM is adequate for ISI elimination. Moreover, compared to the benchmarking scheme of Orthogonal Frequency Division Multiplexing (OFDM), multi-user BS-side DAM achieves higher spectral efficiency and lower Peak-to-Average Power Ratio (PAPR).
{"title":"Double-side delay alignment modulation for multi-user millimeter wave and terahertz communications","authors":"Xingwei Wang , Haiquan Lu , Jieni Zhang , Yong Zeng","doi":"10.1016/j.dcan.2025.04.002","DOIUrl":"10.1016/j.dcan.2025.04.002","url":null,"abstract":"<div><div>Delay Alignment Modulation (DAM) is an innovative broadband modulation technique well-suited for millimeter Wave (mmWave) and Terahertz (THz) massive Multiple-Input Multiple-Output (MIMO) communication systems. Leveraging the high spatial resolution and sparsity of multi-path channels, DAM effectively mitigates Inter-Symbol Interference (ISI) by aligning all multi-path components through a combination of delay pre-compensation (or post-compensation) and path-based beamforming. As such, ISI is eliminated while preserving multi-path power gains. In this paper, we investigate multi-user double-side DAM, which incorporates both delay pre-compensation at the transmitter and post-compensation at the receiver, in contrast to prior works that primarily focus on single-side DAM with only delay pre-compensation. Firstly, we derive the constraint on the number of introduced delays and formulate the corresponding delay pre/post-compensation vectors tailored for multi-user double-side DAM, given a specific number of delay compensations. Furthermore, we demonstrate that when the number of Base Stations (BSs)/User Equipment (UE) antennas is sufficiently large, single-side DAM—where delay compensation is performed only at the BS/UE—is preferable to double-side DAM, since the former results in less ISI to be spatially eliminated. Next, we propose two low-complexity path-based beamforming strategies based on the eigen-beamforming transmission and ISI-Zero Forcing (ZF), respectively. On this basis, we further analyze the achievable sum rates. Simulation results verify that with a sufficiently large number of BS/UE antennas, single-side DAM is adequate for ISI elimination. Moreover, compared to the benchmarking scheme of Orthogonal Frequency Division Multiplexing (OFDM), multi-user BS-side DAM achieves higher spectral efficiency and lower Peak-to-Average Power Ratio (PAPR).</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 1","pages":"Pages 11-24"},"PeriodicalIF":7.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039730","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}
Pub Date : 2026-01-01Epub Date: 2024-12-31DOI: 10.1016/j.dcan.2024.12.008
Subhranshu Sekhar Tripathy , Sujit Bebortta , Mazin Abed Mohammed , Muhammet Deveci , Haydar Abdulameer Marhoon , Radek Martinek
Practical applications of smart cities and the Internet of Things (IoT) have multiplied, posing many difficulties in network performance, dependability, and security. Concerns of accessibility, reliability, sustainability, and security too have arisen correspondingly because of the decentralized character of the smart city and IoT systems. Fog computing offers a foundation for various applications, including cognitive support, health and social services, intelligent transportation systems, and pervasive computing and communications. Fog computing can help enhance these apps' productivity and lower the end-to-end delay experienced by such time-sensitive applications. In this research, we propose a reliable and secure service delivery strategy at the network edge for smart cities. To improve the availability and dependability, along with the security of smart city applications, the approach employs a combined method uniting distributed fog servers in addition to mist servers with the help of an intrusion detection system. Simulation findings suggest a reduction of 40.3% in the delay incurred by each service request for highly dense areas and 60.6% for moderately dense environments. Furthermore, the system has low false-negative rates and high detection and accuracy rates, decreasing service requests 2%.
{"title":"A secure mist-fog-assisted cooperative offloading framework for sustainable smart city development","authors":"Subhranshu Sekhar Tripathy , Sujit Bebortta , Mazin Abed Mohammed , Muhammet Deveci , Haydar Abdulameer Marhoon , Radek Martinek","doi":"10.1016/j.dcan.2024.12.008","DOIUrl":"10.1016/j.dcan.2024.12.008","url":null,"abstract":"<div><div>Practical applications of smart cities and the Internet of Things (IoT) have multiplied, posing many difficulties in network performance, dependability, and security. Concerns of accessibility, reliability, sustainability, and security too have arisen correspondingly because of the decentralized character of the smart city and IoT systems. Fog computing offers a foundation for various applications, including cognitive support, health and social services, intelligent transportation systems, and pervasive computing and communications. Fog computing can help enhance these apps' productivity and lower the end-to-end delay experienced by such time-sensitive applications. In this research, we propose a reliable and secure service delivery strategy at the network edge for smart cities. To improve the availability and dependability, along with the security of smart city applications, the approach employs a combined method uniting distributed fog servers in addition to mist servers with the help of an intrusion detection system. Simulation findings suggest a reduction of 40.3% in the delay incurred by each service request for highly dense areas and 60.6% for moderately dense environments. Furthermore, the system has low false-negative rates and high detection and accuracy rates, decreasing service requests 2%.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 1","pages":"Pages 165-179"},"PeriodicalIF":7.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146189433","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}
Pub Date : 2026-01-01Epub Date: 2025-03-31DOI: 10.1016/j.dcan.2025.03.011
Ailing Zhong , Dapeng Wu , Boran Yang , Ruyan Wang
Computing Power Network (CPN) is a new paradigm that integrates communication, computing, and storage resources to provide services for tasks. However, tasks composed of non-independent subtasks have a preference for the resources required at each stage, which increases the difficulty of heterogeneous resource allocation and reduces the latency performance of CPN services. Motivated by this, this paper jointly optimizes the full-service cycle of tasks, including transmission, task partitioning, and offloading. First, the transmission bandwidth is dynamically configured based on delay sensitivity of tasks. Second, with the real-time information from edge resource clusters and state resource clusters in the network, the optimal partitioning for a computation task is derived. Third, personalized resource allocation schemes are customized for computation and storage tasks respectively. Finally, the impact of resource parameter configuration on the latency violation probability of CPN is revealed. Moreover, compared with the benchmark schemes, our proposed scheme reduces the network latency violation probability by up to 1.17 × in the same network setting.
CPN （Computing Power Network）是一种集成通信、计算和存储资源，为任务提供服务的新范式。然而，由非独立子任务组成的任务对每个阶段所需的资源具有优先性，这增加了异构资源分配的难度，降低了CPN服务的延迟性能。基于此，本文对任务的全服务周期进行了优化，包括传输、任务分区和卸载。首先，根据任务的延迟敏感性动态配置传输带宽。其次，利用网络中边缘资源集群和状态资源集群的实时信息，推导出计算任务的最优划分；第三，分别针对计算任务和存储任务定制个性化的资源分配方案。最后，揭示了资源参数配置对CPN延迟违反概率的影响。此外，与基准方案相比，在相同的网络设置下，我们提出的方案将网络延迟违反概率降低了1.17倍。
{"title":"Heterogeneous resource allocation with latency guarantee for computing power network","authors":"Ailing Zhong , Dapeng Wu , Boran Yang , Ruyan Wang","doi":"10.1016/j.dcan.2025.03.011","DOIUrl":"10.1016/j.dcan.2025.03.011","url":null,"abstract":"<div><div>Computing Power Network (CPN) is a new paradigm that integrates communication, computing, and storage resources to provide services for tasks. However, tasks composed of non-independent subtasks have a preference for the resources required at each stage, which increases the difficulty of heterogeneous resource allocation and reduces the latency performance of CPN services. Motivated by this, this paper jointly optimizes the full-service cycle of tasks, including transmission, task partitioning, and offloading. First, the transmission bandwidth is dynamically configured based on delay sensitivity of tasks. Second, with the real-time information from edge resource clusters and state resource clusters in the network, the optimal partitioning for a computation task is derived. Third, personalized resource allocation schemes are customized for computation and storage tasks respectively. Finally, the impact of resource parameter configuration on the latency violation probability of CPN is revealed. Moreover, compared with the benchmark schemes, our proposed scheme reduces the network latency violation probability by up to 1.17 × in the same network setting.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 1","pages":"Pages 25-37"},"PeriodicalIF":7.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039718","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}
Location-Based Services (LBS) have greatly improved efficiency and functionality in various domains, but privacy and security concerns remain due to the centralized nature of many existing systems. To address these issues, this paper introduces the V-Track system, a decentralized architecture using blockchain technology for reliable vehicle location verification. By integrating GPS devices (SparkFun GPS NEO-M9), IoT-enabled sensors, and a Cosmos blockchain-based ledger (network of interconnected blockchains), V-Track aims to solve centralized LBS problems. Through rigorous simulation experiments, this paper evaluates the performance and security of the V-Track system and demonstrates its potential to provide reliable location verification while preserving user privacy. This paper makes significant contributions by presenting V-Track as a decentralized solution to centralized LBS privacy and security problems, enhancing reliability and trustworthiness through blockchain integration, improving tracking mechanisms with GPS devices and IoT sensors for improved accuracy, and providing a privacy-preserving alternative to centralized LBS through its decentralized design and use of blockchain technology. These advancements hold promise for applications across multiple sectors, including logistics, supply chain management, urban planning, and emerging fields such as autonomous vehicles and augmented reality.
{"title":"V-track: Blockchain-enabled IoT system for reliable vehicle location verification","authors":"Mritunjay Shall Peelam, Kunjan Shah, Vinay Chamola","doi":"10.1016/j.dcan.2024.08.004","DOIUrl":"10.1016/j.dcan.2024.08.004","url":null,"abstract":"<div><div>Location-Based Services (LBS) have greatly improved efficiency and functionality in various domains, but privacy and security concerns remain due to the centralized nature of many existing systems. To address these issues, this paper introduces the V-Track system, a decentralized architecture using blockchain technology for reliable vehicle location verification. By integrating GPS devices (SparkFun GPS NEO-M9), IoT-enabled sensors, and a Cosmos blockchain-based ledger (network of interconnected blockchains), V-Track aims to solve centralized LBS problems. Through rigorous simulation experiments, this paper evaluates the performance and security of the V-Track system and demonstrates its potential to provide reliable location verification while preserving user privacy. This paper makes significant contributions by presenting V-Track as a decentralized solution to centralized LBS privacy and security problems, enhancing reliability and trustworthiness through blockchain integration, improving tracking mechanisms with GPS devices and IoT sensors for improved accuracy, and providing a privacy-preserving alternative to centralized LBS through its decentralized design and use of blockchain technology. These advancements hold promise for applications across multiple sectors, including logistics, supply chain management, urban planning, and emerging fields such as autonomous vehicles and augmented reality.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 1","pages":"Pages 119-133"},"PeriodicalIF":7.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079577","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}
Pub Date : 2026-01-01Epub Date: 2025-04-29DOI: 10.1016/j.dcan.2025.04.009
Chi Zhang , Tao Shen , Fenhua Bai , Kai Zeng , Xiaohui Zhang , Bin Cao
The global surge in Artificial Intelligence (AI) has been triggered by the impressive performance of deep-learning models based on the Transformer architecture. However, the efficacy of such models is increasingly dependent on the volume and quality of data. Data are often distributed across institutions and companies, making cross-organizational data transfer vulnerable to privacy breaches and subject to privacy laws and trade secret regulations. These privacy and security concerns continue to pose major challenges to collaborative training and inference in multi-source data environments. These challenges are particularly significant for Transformer models, where the complex internal encryption computations drastically reduce computational efficiency, ultimately threatening the model's practical applicability. We hence introduce Secformer, an innovative architecture specifically designed to protect the privacy of Transformer-like models. Secformer separates the encoder and decoder modules, enabling the decomposition of computation flows in Transformer-like models and their efficient mapping to Multi-Party Computation (MPC) protocols. This design effectively addresses privacy leakage issues during the collaborative computation process of Transformer models. To prevent performance degradation caused by encrypted attention modules, we propose a modular design strategy that optimizes high-level components by reconstructing low-level operators. We further analyze the security of Secformer's core components, presenting security definitions and formal proofs. We construct a library of fundamental operators and core modules using atomic-level component designs as the basic building blocks for encoders and decoders. Moreover, these components can serve as foundational operators for other Transformer-like models. Extensive experimental evaluations demonstrate Secformer's excellent performance while preserving privacy and offering universal adaptability for Transformer-like models.
{"title":"Secformer: Privacy-preserving atomic-level componentized transformer-like model with MPC","authors":"Chi Zhang , Tao Shen , Fenhua Bai , Kai Zeng , Xiaohui Zhang , Bin Cao","doi":"10.1016/j.dcan.2025.04.009","DOIUrl":"10.1016/j.dcan.2025.04.009","url":null,"abstract":"<div><div>The global surge in Artificial Intelligence (AI) has been triggered by the impressive performance of deep-learning models based on the Transformer architecture. However, the efficacy of such models is increasingly dependent on the volume and quality of data. Data are often distributed across institutions and companies, making cross-organizational data transfer vulnerable to privacy breaches and subject to privacy laws and trade secret regulations. These privacy and security concerns continue to pose major challenges to collaborative training and inference in multi-source data environments. These challenges are particularly significant for Transformer models, where the complex internal encryption computations drastically reduce computational efficiency, ultimately threatening the model's practical applicability. We hence introduce Secformer, an innovative architecture specifically designed to protect the privacy of Transformer-like models. Secformer separates the encoder and decoder modules, enabling the decomposition of computation flows in Transformer-like models and their efficient mapping to Multi-Party Computation (MPC) protocols. This design effectively addresses privacy leakage issues during the collaborative computation process of Transformer models. To prevent performance degradation caused by encrypted attention modules, we propose a modular design strategy that optimizes high-level components by reconstructing low-level operators. We further analyze the security of Secformer's core components, presenting security definitions and formal proofs. We construct a library of fundamental operators and core modules using atomic-level component designs as the basic building blocks for encoders and decoders. Moreover, these components can serve as foundational operators for other Transformer-like models. Extensive experimental evaluations demonstrate Secformer's excellent performance while preserving privacy and offering universal adaptability for Transformer-like models.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 1","pages":"Pages 86-100"},"PeriodicalIF":7.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079575","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}
Pub Date : 2026-01-01Epub Date: 2025-07-02DOI: 10.1016/j.dcan.2025.06.014
Muhammad Muzamil Aslam , Wasswa Shafik , Ahmad Fathan Hidayatullah , Kassim Kalinaki , Haji Gul , Rufai Yusuf Zakari , Ali Tufail
The concept of Cyber-Physical Systems (CPS) enables the creation of a complex network that includes sensors integrated into vehicles and infrastructure, facilitating seamless data acquisition and transfer. This review examines the convergence of CPS and Industry 4.0 in the smart transportation sector, highlighting their transformative impact on Intelligent Transportation Systems (ITS) operations. It explores the integration of Industry 4.0 and CPS technologies in intelligent transportation, highlighting their roles in enhancing efficiency, safety, and sustainability. A systematic framework is proposed for developing, implementing, and managing these technologies in the transportation industry. Moreover, the review discusses frequent obstacles during technology integration in transportation and presents future research trends and innovations in intelligent transportation operations post-Industry 4.0 and CPS integration. Lastly, it emphasizes the critical need for standardized protocols and encryption methodologies to enhance the security of communication and data exchange among CPS components in transportation infrastructure.
{"title":"Intelligent Transportation Systems: A Critical Review of Integration of Cyber-Physical Systems (CPS) and Industry 4.0","authors":"Muhammad Muzamil Aslam , Wasswa Shafik , Ahmad Fathan Hidayatullah , Kassim Kalinaki , Haji Gul , Rufai Yusuf Zakari , Ali Tufail","doi":"10.1016/j.dcan.2025.06.014","DOIUrl":"10.1016/j.dcan.2025.06.014","url":null,"abstract":"<div><div>The concept of Cyber-Physical Systems (CPS) enables the creation of a complex network that includes sensors integrated into vehicles and infrastructure, facilitating seamless data acquisition and transfer. This review examines the convergence of CPS and Industry 4.0 in the smart transportation sector, highlighting their transformative impact on Intelligent Transportation Systems (ITS) operations. It explores the integration of Industry 4.0 and CPS technologies in intelligent transportation, highlighting their roles in enhancing efficiency, safety, and sustainability. A systematic framework is proposed for developing, implementing, and managing these technologies in the transportation industry. Moreover, the review discusses frequent obstacles during technology integration in transportation and presents future research trends and innovations in intelligent transportation operations post-Industry 4.0 and CPS integration. Lastly, it emphasizes the critical need for standardized protocols and encryption methodologies to enhance the security of communication and data exchange among CPS components in transportation infrastructure.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 1","pages":"Pages 143-164"},"PeriodicalIF":7.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079576","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}
Pub Date : 2026-01-01Epub Date: 2024-04-15DOI: 10.1016/j.dcan.2024.04.002
Daozhong Feng , Jiajian Lai , Wenxuan Wei , Bin Hao
Transit managers can use Intelligent Transportation System technologies to access large amounts of data to monitor network status. However, the presentation of the data lacks structural information. Existing single-network description technologies are ineffective in representing the temporal and spatial characteristics simultaneously. Therefore, there is a need for complementary methods to address these deficiencies. To address these limitations, this paper proposes an approach that combines Network Snapshots and Temporal Paths for the scheduled system. A dual information network is constructed to assess the degree of operational deviation considering the planning tasks. To validate the effectiveness, discussions are conducted through a modified cosine similarity calculation on theoretical analysis, delay level description, and the ability to identify abnormal dates. Compared to some state-of-the-art methods, the proposed method achieves an average Spearman delay correlation of 0.847 and a relative distance of 3.477. Furthermore, case analyses are invested in regions of China's Mainland, Europe, and the United States, investigating both the overall and sub-regional network fluctuations. To represent the impact of network fluctuations in sub-regions, a response loss value was developed. The times that are prone to fluctuations are also discussed through the classification of time series data. The research can offer a novel approach to system monitoring, providing a research direction that utilizes individual data combined to represent macroscopic states. Our code will be released at https://github.com/daozhong/STPN.git.
{"title":"A novel deviation measurement for scheduled intelligent transportation system via comparative spatial-temporal path networks","authors":"Daozhong Feng , Jiajian Lai , Wenxuan Wei , Bin Hao","doi":"10.1016/j.dcan.2024.04.002","DOIUrl":"10.1016/j.dcan.2024.04.002","url":null,"abstract":"<div><div>Transit managers can use Intelligent Transportation System technologies to access large amounts of data to monitor network status. However, the presentation of the data lacks structural information. Existing single-network description technologies are ineffective in representing the temporal and spatial characteristics simultaneously. Therefore, there is a need for complementary methods to address these deficiencies. To address these limitations, this paper proposes an approach that combines Network Snapshots and Temporal Paths for the scheduled system. A dual information network is constructed to assess the degree of operational deviation considering the planning tasks. To validate the effectiveness, discussions are conducted through a modified cosine similarity calculation on theoretical analysis, delay level description, and the ability to identify abnormal dates. Compared to some state-of-the-art methods, the proposed method achieves an average Spearman delay correlation of 0.847 and a relative distance of 3.477. Furthermore, case analyses are invested in regions of China's Mainland, Europe, and the United States, investigating both the overall and sub-regional network fluctuations. To represent the impact of network fluctuations in sub-regions, a response loss value was developed. The times that are prone to fluctuations are also discussed through the classification of time series data. The research can offer a novel approach to system monitoring, providing a research direction that utilizes individual data combined to represent macroscopic states. Our code will be released at <span><span>https://github.com/daozhong/STPN.git</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 1","pages":"Pages 101-118"},"PeriodicalIF":7.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140757321","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}
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