Computer Networks最新文献

Physical layer security techniques for grant-free massive Machine-Type Communications in 5G and beyond: A survey, challenges, and future directions

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-04-05 DOI: 10.1016/j.comnet.2025.111268

Uchenna P. Enwereonye, Ahmad Salehi Shahraki, Hooman Alavizadeh, A.S.M. Kayes

{"title":"Physical layer security techniques for grant-free massive Machine-Type Communications in 5G and beyond: A survey, challenges, and future directions","authors":"Uchenna P. Enwereonye, Ahmad Salehi Shahraki, Hooman Alavizadeh, A.S.M. Kayes","doi":"10.1016/j.comnet.2025.111268","DOIUrl":"10.1016/j.comnet.2025.111268","url":null,"abstract":"<div><div>The future of smart cities, industrial automation, and connected vehicles is heavily reliant on advanced communication technologies. These technologies, particularly massive Machine-Type Communication (mMTC), are the backbone of the many connected devices required for these applications. Grant -free access in 5G and beyond, while enhancing transmission efficiency by eliminating the need for permission requests, also introduces significant security risks. These risks, such as unauthorised access, data interception, and interference due to the absence of centralised control, are of paramount importance. Physical layer security (PLS) techniques, with their ability to exploit the unique properties of wireless channels to bolster communication security, offer a promising solution. This paper provides a comprehensive review of PLS techniques for securing grant-free mMTC, comparing different approaches and exploring the challenges of their integration. Our findings lay the groundwork for future research and the practical implementation of advanced security solutions in grant-free mMTC, a development that will also enhance the security of advanced 5G and 6G networks.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"264 ","pages":"Article 111268"},"PeriodicalIF":4.4,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783803","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}

引用次数: 0

Enhancing trust and collaboration: A reputation-driven mechanism for cross-chain IoT data sharing

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-04-04 DOI: 10.1016/j.comnet.2025.111266

Runqun Xiong , Jing Cheng , Jiahang Pu , Xirui Dong , Ciyuan Chen , Zhuqing Xu

{"title":"Enhancing trust and collaboration: A reputation-driven mechanism for cross-chain IoT data sharing","authors":"Runqun Xiong , Jing Cheng , Jiahang Pu , Xirui Dong , Ciyuan Chen , Zhuqing Xu","doi":"10.1016/j.comnet.2025.111266","DOIUrl":"10.1016/j.comnet.2025.111266","url":null,"abstract":"<div><div>Cross-chain data sharing in the Internet of Things (IoT) has become a critical challenge due to the isolation of industry-specific blockchains and the lack of trust mechanisms between heterogeneous networks. This issue is particularly important as IoT data sharing enables cross-industry collaboration, unlocks data value, and fosters innovation in applications such as smart cities and intelligent transportation. Existing solutions, including notary mechanisms, side-chains, and relay chains, often suffer from centralization issues, limited scalability, or inadequate incentives for active participation, making them insufficient to address the dynamic and large-scale requirements of IoT ecosystems. To tackle this problem, this paper proposes a reputation-based incentive mechanism for cross-chain data sharing, which integrates a main-subchain architecture with a two-stage notary group election algorithm based on evolutionary game theory. Additionally, a Stackelberg game is employed to model interactions between data producers and consumers, optimizing data pricing strategies and incentivizing trustworthy sharing. The proposed framework is evaluated through extensive simulations on a star-topology blockchain network, testing its scalability, fairness, and effectiveness. Results demonstrate that the mechanism not only mitigates centralization problems but also enhances trust, collaboration, and efficiency across heterogeneous blockchains, providing a robust foundation for IoT data-sharing applications.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"264 ","pages":"Article 111266"},"PeriodicalIF":4.4,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783819","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}

引用次数: 0

Optimal action-selection optimization of wireless networks based on virtual representation

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-04-01 DOI: 10.1016/j.comnet.2025.111258

Rafael Oliveira , Duarte Raposo , Miguel Luís , Susana Sargento

{"title":"Optimal action-selection optimization of wireless networks based on virtual representation","authors":"Rafael Oliveira , Duarte Raposo , Miguel Luís , Susana Sargento","doi":"10.1016/j.comnet.2025.111258","DOIUrl":"10.1016/j.comnet.2025.111258","url":null,"abstract":"<div><div>Modern smart homes are becoming increasingly complex due to the growing number of connected wireless devices and the need for a fast, stable Internet connection. Tri-band Wi-Fi 6E addresses these demands by reducing network congestion and enhancing performance across the 2.4, 5 and 6 GHz bands. However, improper channel management can lead to frequent interference and network instability. This work introduces a Wi-Fi management solution that uses reinforcement learning to automatically optimize network configurations based on the observed interference levels. The Wi-Fi network is mapped to a virtual environment to simulate different scenarios with real data acquired from the network, allowing the system to learn and improve without disrupting the actual network. Practical tests were conducted in four residential network layouts, including star and daisy chain topologies. The solution effectively reduces the number of hops, improves the throughput in longer paths from the gateway to clients, adapts to unforeseen network dynamics in the presence of Ethernet clients and adjusts the configuration as clients move within the home. The results demonstrate improved network capacity and responsiveness compared to default configurations. In the best cases, clients achieved rates of up to 1 Gbps, round-trip times as low as 10 ms, and efficient airtime distribution across the three frequency bands. The proposed approach provides a robust and automated solution to address the challenges of domestic wireless networking and paves the way to more sophisticated virtualization solutions for end users at home.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"264 ","pages":"Article 111258"},"PeriodicalIF":4.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760066","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}

引用次数: 0

Online participant selection incorporating coverage quality and participant ability for edge-aided vehicular crowdsensing

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-04-01 DOI: 10.1016/j.comnet.2025.111265

Mengge Li , Miao Ma , Liang Wang , Bo Yang

{"title":"Online participant selection incorporating coverage quality and participant ability for edge-aided vehicular crowdsensing","authors":"Mengge Li , Miao Ma , Liang Wang , Bo Yang","doi":"10.1016/j.comnet.2025.111265","DOIUrl":"10.1016/j.comnet.2025.111265","url":null,"abstract":"<div><div>Recently, the edge-aided vehicular crowdsensing (EAVC) system has become a promising data collection mode, which utilizes vehicles to collect sensing data under the guidance of edge servers. Participant selection is a fundamental problem in vehicular crowdsensing. The available relevant schemes are unsuitable for newly arrived participants, ignore the differentiated sensing requirements of different areas, and underestimate heterogeneity among participants, which seriously damages the service quality. To handle these problems, this paper proposes an improved reinforcement learning-based online participant selection scheme incorporating coverage quality and participant ability (PSCQA) in EAVC. Coverage quality considering different spatiotemporal partitions is formulated based on the entropy theory to measure coverage uniformity of all areas and the coverage degree of the hotspot areas. Participant ability is designed by combining data quality, movement predictability, and priorities of passing areas to comprehensively measure performance differences among participants. In PSCQA, the coverage quality and ability of the selected participants are optimized through two separate value functions. In particular, participants are dynamically grouped into vehicle clusters based on the similarity of their trajectories to solve the state explosion problem that plagues traditional Q-learning. Simulation results on a real-world dataset demonstrate that the proposed PSCQA outperforms other reinforcement learning-based online participant selection schemes and traditional offline participant selection schemes.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"264 ","pages":"Article 111265"},"PeriodicalIF":4.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768905","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}

引用次数: 0

Trust-based fog-blockchain model for scalable authentication in smart cities 基于信任的雾区块链模型，用于智能城市中的可扩展身份验证

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-03-31 DOI: 10.1016/j.comnet.2025.111278

Osama A. Khashan

{"title":"Trust-based fog-blockchain model for scalable authentication in smart cities","authors":"Osama A. Khashan","doi":"10.1016/j.comnet.2025.111278","DOIUrl":"10.1016/j.comnet.2025.111278","url":null,"abstract":"<div><div>In smart cities, ensuring robust authentication, security, and scalability of infrastructure presents significant challenges. Traditional centralized authentication methods expose vulnerabilities and increase energy consumption, particularly in resource-constrained IoT nodes. Moreover, existing blockchain-based authentication systems encounter substantial overhead, delays, and complexities, compromising their effectiveness in diverse environments. A critical issue in real-time smart systems is the significant authentication delays caused by the high volume of requests processed by the blockchain. To address these challenges, we propose an innovative blockchain architecture that connects distributed fog servers for seamless IoT node authentication within smart-city networks. Our model integrates trust-based analyses, encompassing the behavior and data trust evaluations of the IoT at fog servers, to fortify security by detecting malicious nodes and tampered data early in the process. This process streamlines verification by reducing the influx of untrusted data during consensus, ensuring only the most reliable data advances for blockchain operations, and enhancing efficiency and reliability. This architecture guarantees data confidentiality and integrity through lightweight encryption and digital certification. It fosters scalability, seamless communication, and information sharing among smart city entities, facilitating internetwork node identification across a spectrum of smart systems. Performance assessment of the proposed model revealed notable improvements in computation cost, execution time, and power consumption. Our findings revealed a network lifetime enhancement of up to 35 % compared with centralized and blockchain schemes. Furthermore, a security assessment confirmed the effectiveness of the model in preventing tampering and various attacks, thereby satisfying the stringent security requirements of smart cities.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"264 ","pages":"Article 111278"},"PeriodicalIF":4.4,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776705","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}

引用次数: 0

Detecting attacks in Fog and cloud computing environments using Deep Learning: A systematic literature review

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-03-30 DOI: 10.1016/j.comnet.2025.111269

Erivan Laranjeira Pimentel, Cristiano Antonio de Souza, Carlos Becker Westphall

{"title":"Detecting attacks in Fog and cloud computing environments using Deep Learning: A systematic literature review","authors":"Erivan Laranjeira Pimentel, Cristiano Antonio de Souza, Carlos Becker Westphall","doi":"10.1016/j.comnet.2025.111269","DOIUrl":"10.1016/j.comnet.2025.111269","url":null,"abstract":"<div><div>The mass use of the Internet of Things (IoT) brings huge benefits to the most diverse areas, increasing productivity and facilitating processes. Due to the huge growth in IoT applications, there has also been an increase in attackers interest in breaching the security of these devices. IoT devices have low processing power and generally generate large amounts of data, characteristics that make it difficult to implement complex security techniques on these devices. Cloud computing and fog computing are emerging <u>as</u> alternatives that can overcome existing hardware limitations. Thus, security implementations that were previously limited by IoT computing resources began to be deployed more frequently. Although approaches based on Machine Learning (ML) have proven to be efficient in intrusion detection, over time they have proved to be poorly adapted to the large amounts of data typical of IoT environments. Given this scenario, there is a clear need for more effective security solutions to combat attacks. This study presents a systematic literature review focused on deep learning (DL) techniques applied to intrusion detection in fog/cloud computing environments. This review identified emerging trends, open questions and gaps in existing work, as well as evaluating the main DL models, types of attacks most investigated, databases used, detection models and solutions implemented in the literature. The analysis also discusses the limitations of current methods, and the areas that need further investigation. As its main contribution, the study highlights seven important research gaps, pointing to potential directions for future research.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"264 ","pages":"Article 111269"},"PeriodicalIF":4.4,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783802","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}

引用次数: 0

A demand aware services placement model in Pervasive Edge Computing

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-03-29 DOI: 10.1016/j.comnet.2025.111254

Nikolaos Tymplalexis , Kostas Kolomvatsos , Christos Anagnostopoulos

{"title":"A demand aware services placement model in Pervasive Edge Computing","authors":"Nikolaos Tymplalexis , Kostas Kolomvatsos , Christos Anagnostopoulos","doi":"10.1016/j.comnet.2025.111254","DOIUrl":"10.1016/j.comnet.2025.111254","url":null,"abstract":"<div><div>Nowadays, one can observe the convergence of the Internet of Things (IoT) and Edge Computing (EC) infrastructures towards establishing a data collection and processing ecosystem in close proximity to end users. The aim is to enhance the performance of the supported applications by reducing the latency in data processing and service delivery. Various services can be employed to facilitate the execution of tasks prompted by end users or any type of external applications. Those services are mainly present at EC nodes that become the hosts of the data collected by IoT devices, the executors of the desired tasks and the intermediaries when transferring the discussed data to the Cloud back end. It is obvious that the implementation of an efficient framework for managing services across distributed edge nodes becomes imperative especially if we bear in mind that nodes are constrained devices and cannot host numerous services. In this paper, we introduce a proactive model designed to allocate the available services to core parts of the EC ecosystem based on the observed demand. This will give us the opportunity to determine ‘where’ to place any individual service putting it in locations (i.e., in EC nodes) where an increased demand is identified, while saving resources by restricting the number of nodes that become the final hosts (to avoid the flooding of the network). The paper delves into the evaluation of the proposed model, offering a comparative analysis with a baseline scheme utilizing real datasets. Through the envisioned experimental validation, the paper demonstrates that the proposed approach enhances the ability of diverse engaged edge nodes to accurately deduce the appropriate location for service placement.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"264 ","pages":"Article 111254"},"PeriodicalIF":4.4,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768906","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}

引用次数: 0

Privacy-preserving cross-domain point-of-interests recommendation based on friendship in LBSs

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-03-28 DOI: 10.1016/j.comnet.2025.111243

Lulu Han , Weiqi Luo , Anjia Yang , Yudan Cheng , Junzuo Lai , Fang Han , Jiaquan Shen , Yongxin Zhang

{"title":"Privacy-preserving cross-domain point-of-interests recommendation based on friendship in LBSs","authors":"Lulu Han , Weiqi Luo , Anjia Yang , Yudan Cheng , Junzuo Lai , Fang Han , Jiaquan Shen , Yongxin Zhang","doi":"10.1016/j.comnet.2025.111243","DOIUrl":"10.1016/j.comnet.2025.111243","url":null,"abstract":"<div><div>As one of the location-based services (LBSs), point-of-interests (POI) recommendations make users’ daily life more and more convenient. Due to the cold start and data sparsity problems, it is not easy to achieve accurate and efficient POI recommendations, especially for new users. To solve these problems, other domains (or source domains) with sufficient data can be utilized to assist POI recommendations in the target domain. However, source domains are always unwilling to share their data with the POI service provider when considering privacy issues and some regulations. Although some existing schemes have been proposed to address privacy problems in the cross-domain scenario, accurate recommendation, running in the outsourced environment, and direct utility of data from the source domain are not achieved simultaneously. Therefore, we propose a privacy-preserving cross-domain POI recommendation scheme based on friendship in LBSs, where social and geographical influence are both considered. Specifically, based on the symmetric homomorphic encryption (SHE), we first propose a secure Jaccard similarity (SJS) protocol to compute the social and geographical similarities between users in an encrypted way. Second, using the SHE and our SJS protocol, we develop a privacy-preserving cross-domain POI recommendation scheme in outsourced environments. Finally, we analyze the security of our scheme in the semi-honest model and prove that the data privacy of the source domain and target domain is well protected. We also evaluate the performance of our scheme on synthetic and real-world datasets and demonstrate the effectiveness of our scheme.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"264 ","pages":"Article 111243"},"PeriodicalIF":4.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748077","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}

引用次数: 0

Enhancing IoT performance in wireless and mobile networks through named data networking (NDN) and edge computing integration

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-03-28 DOI: 10.1016/j.comnet.2025.111267

Ahmed M. Alwakeel

{"title":"Enhancing IoT performance in wireless and mobile networks through named data networking (NDN) and edge computing integration","authors":"Ahmed M. Alwakeel","doi":"10.1016/j.comnet.2025.111267","DOIUrl":"10.1016/j.comnet.2025.111267","url":null,"abstract":"<div><div>Available online The rapid expansion of the Internet of Things (IoT) in wireless and mobile networks demands novel approaches for efficient data transmission and management. Traditional IP-based networking architectures struggle to meet the high-speed, low-latency, and scalable requirements of IoT. Named Data Networking (NDN), a content-centric networking paradigm, provides an alternative by focusing on data retrieval based on content names rather than device addresses. However, while NDN offers significant advantages in reducing latency and improving data dissemination, its integration with edge computing for real-time IoT applications remains suboptimal due to challenges in dynamic resource allocation, routing efficiency, and robustness under uncertain network conditions. This paper proposes a novel adaptive NDN-Edge Computing framework that dynamically optimizes data retrieval, caching, and computational resource allocation. Unlike prior studies that focus solely on theoretical models or static configurations, our framework introduces a multi-objective optimization model for balancing latency, reliability, and energy efficiency in IoT environments. Additionally, we formulate a robust optimization approach to ensure network resilience against unpredictable traffic surges, topology changes, and edge node failures. Through extensive simulations and real-world case studies, we demonstrate that the proposed integration significantly improves latency (up to 25 % reduction), energy efficiency (15 % improvement), and cache hit ratio (20 % increase) compared to conventional NDN and edge computing approaches. This work contributes to the ongoing research by providing a scalable, adaptive, and resilient NDN-edge computing framework that enhances IoT data processing while addressing critical limitations of existing solutions. Future work will focus on security enhancements and the integration of blockchain for decentralized trust management in IoT ecosystems.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"264 ","pages":"Article 111267"},"PeriodicalIF":4.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748076","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}

引用次数: 0

Blockchain-based multiple auditing scheme against cheating owner in clouds

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-03-27 DOI: 10.1016/j.comnet.2025.111214

Jifang Wang , Shangping Wang , Duo Zhang , Qian Zhang , Yinjuan Deng

{"title":"Blockchain-based multiple auditing scheme against cheating owner in clouds","authors":"Jifang Wang , Shangping Wang , Duo Zhang , Qian Zhang , Yinjuan Deng","doi":"10.1016/j.comnet.2025.111214","DOIUrl":"10.1016/j.comnet.2025.111214","url":null,"abstract":"<div><div>Along with the commonplace of cloud outsourcing services, the problem of auditing the integrity of outsourced data without downloading has attracted much attention increasingly. However, in most existing auditing schemes, the audit only focuses on resisting undependable cloud server, rarely considers the problem of resisting cheating owner. An unreliable data owner may store the data not the same as it claimed for interest. Even worse, an undependable owner may deliver a sham message deliberately to avoid paying server for service or to cheat its deposit. To solve this problem, we propose a blockchain-based multiple auditable scheme against cheating owner by constructing a novel incremental structure, that allows for low computation and communication overheads, while providing a continuous natural flow of joint verification between storage parties over time. Specifically, our scheme is a two-way verification protocol that makes both parties consistently dependable. Besides, the incremental structure that uses a reversed recursive hash chain structure combined with blockchain and aggregate signature, makes our scheme more suitable for big data auditing. Smart contract is deployed to realize a central-free mechanism of rewards and penalties. The security analysis and simulation experiment demonstrate that the proposal is secure, dependable, efficient and practical.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"263 ","pages":"Article 111214"},"PeriodicalIF":4.4,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725553","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}

引用次数: 0