{"title":"A systematic literature review on spectrum detection for Cognitive Radio-Internet of Things networks","authors":"Khadija Lahrouni , Hayat Semlali , Guillaume Andrieux , Jean-François Diouris , Abdelilah Ghammaz","doi":"10.1016/j.adhoc.2025.103857","DOIUrl":"10.1016/j.adhoc.2025.103857","url":null,"abstract":"<div><div>The exponential growth of Internet of Things (IoT) devices has created a huge demand for Radio Frequency (RF) spectrum, only exacerbating the current congestion and shortage situation. This is where Cognitive Radio-Internet of Things (CR-IoT) systems come into play, which promises to bring in the functionality of dynamically managing spectrum resources to provide better spectral efficiency by recognizing and exploiting unused frequency bands, or spectrum holes. This systematic literature review investigates the integration of Cognitive Radio (CR) functionalities within IoT networks, focusing particularly on spectrum sensing techniques. Whereas conventional approaches rely on spectrum usage measurements in the frequency domain, temporal slots detection addresses a scarcely touched asset, i.e., predicting spectrum availability over time. Through an analysis of the literature, this paper brings out the advantages of integrating CR into IoT networks and reviews the prominent spectrum sensing techniques in CR-IoT scenarios. Moreover, by addressing the current research gaps in the review, especially from a temporal-aligned spectrum sensing perspective, we particularly highlight the gap of the limited attention to temporal spectrum sensing and suggests future directions for optimizing both frequency and temporal spectrum prediction to improve CR-IoT network performance.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"175 ","pages":"Article 103857"},"PeriodicalIF":4.4,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143847329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ad Hoc NetworksPub Date : 2025-04-11DOI: 10.1016/j.adhoc.2025.103869
Biao Xie , Zhendong Wang , Zhiyuan Zeng , Daojing He , Sammy Chan
{"title":"DTKD-IDS: A dual-teacher knowledge distillation intrusion detection model for the industrial internet of things","authors":"Biao Xie , Zhendong Wang , Zhiyuan Zeng , Daojing He , Sammy Chan","doi":"10.1016/j.adhoc.2025.103869","DOIUrl":"10.1016/j.adhoc.2025.103869","url":null,"abstract":"<div><div>While advances in technology have brought great opportunities for the development of the Industrial Internet of Things (IIoT), cybersecurity risks are also increasing. Intrusion detection is a key technology to ensure the security and smooth operation of the Internet of Things (IoT), but owing to the resource constraints of IIoT devices, intrusion detection solutions need to be targeted and customized for the IIoT. This paper proposes a dual teacher knowledge distillation intrusion detection model called DTKD-IDS, which improves the performance of anomaly detection, accelerates the detection speed of the model, and reduces the complexity of the model. Specifically, To make the distillation process more efficient and stable, DTKD-IDS outputs a data prototype vector after each convolutional layer of the student network and the first teacher network. On the basis of these two prototype vectors, the student model extracts the most valuable knowledge from the structurally similar first teacher model. We name this process prototype distillation. In addition, we weight the extracted knowledge on the basis of the final classification loss of the two teacher networks and adaptively adjust the weights of the two teacher knowledge extractions during the training process to provide more accurate output distributions to guide the student network. This process is referred to as complementary distillation. During the training phase, we design a stable loss function to improve training efficiency. Through knowledge distillation, the model size and the number of parameters decreased by about 250 and 20 times compared to the first model, and by about 30 and 4 times compared to the second teacher model, while maintaining high detection performance. Numerous experimental results have shown that on the X-IIoTID, NSL-KDD and CICDDoS2019 datasets, the performance indicators of DTKD-IDS are improved compared with the traditional deep learning methods and the latest first-class models.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"174 ","pages":"Article 103869"},"PeriodicalIF":4.4,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143834497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ad Hoc NetworksPub Date : 2025-04-09DOI: 10.1016/j.adhoc.2025.103865
Xiao Liu , Li Liang , Zhencai Tan , Jining Chen , Gaoxiang Li
{"title":"An adaptive trust threshold based on Q-Learning for detecting intelligent attacks in vehicular Ad-Hoc Networks","authors":"Xiao Liu , Li Liang , Zhencai Tan , Jining Chen , Gaoxiang Li","doi":"10.1016/j.adhoc.2025.103865","DOIUrl":"10.1016/j.adhoc.2025.103865","url":null,"abstract":"<div><div>Due to the intelligence of attack, some malicious nodes of the Vehicular Ad-Hoc Networks (VANETs) can evade detection and reconnaissance, which poses a huge security threat to the network security. With considering the sufficient adaptability and limited resources consumption in a small state space, a Q-Learning based adaptive trust threshold control strategy (QART) is proposed to balance the detection efficiency of the malicious vehicle and the false alarm of the normal vehicle. Compared with the existing intelligent attack detection schemes, the detection efficiency of the malicious vehicle is higher and the false alarm of the normal vehicle is lower under the proposed strategy. Finally, the experimental results verify that the proposed strategy can identify malicious vehicles in time and effectively reduces false alarms.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"175 ","pages":"Article 103865"},"PeriodicalIF":4.4,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143851408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ad Hoc NetworksPub Date : 2025-04-09DOI: 10.1016/j.adhoc.2025.103854
Ming Li , Furong Xu , Yuqin Wu , Jianshan Zhang , Weitao Xu , Yuezhong Wu
{"title":"Real-time task dispatching and scheduling in serverless edge computing","authors":"Ming Li , Furong Xu , Yuqin Wu , Jianshan Zhang , Weitao Xu , Yuezhong Wu","doi":"10.1016/j.adhoc.2025.103854","DOIUrl":"10.1016/j.adhoc.2025.103854","url":null,"abstract":"<div><div>Edge computing brings computing resources closer to the Internet of Things (IoT) devices, significantly reducing transmission latency and bandwidth usage. However, the limited resources of edge servers require efficient management. Serverless computing meets this demand through its elastic resource provisioning, leading to the emergence of serverless edge computing—a promising computing paradigm. Despite its potential, real-time task dispatching and scheduling in the highly complex and dynamic environment of serverless edge computing present significant challenges. On the one hand, task execution requires not only sufficient CPU resources but also free containers; on the other hand, tasks are typically event-driven, with strong burstiness and high concurrency, and impose stringent demands on fast decision-making. To address these challenges, we propose a real-time task dispatching and scheduling method, aiming to maximize the satisfaction rate of Service Level Objectives (SLOs) for tasks. First, we design a task dispatching algorithm named Adaptive Deep Reinforcement Learning (ADRL). This algorithm can quickly decide the execution position of tasks based on coarse information and effectively adapt to the changes in available servers in dynamic environments. Second, we propose a task scheduling algorithm named Warm-aware Shortest Remaining Idle Time (WSRIT), which guides the edge servers to schedule the tasks in the request queue based on the tasks’ remaining idle time and the state of the warm containers. Considering the limited storage space of the edge servers, we further introduce a container replacement algorithm named Low Priority First (LPF) to ensure smooth container launches. Extensive simulation experiments are conducted based on Azure datasets. The results show that our methodcan improve the satisfaction rate of SLOs by 12.57<span><math><mo>∼</mo></math></span>41.87% and achieve the lowest cold start rate compared to existing methods.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"174 ","pages":"Article 103854"},"PeriodicalIF":4.4,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ad Hoc NetworksPub Date : 2025-04-05DOI: 10.1016/j.adhoc.2025.103844
Chang Deng , Xiuwen Fu , Savaglio Claudio , Giancarlo Fortino
{"title":"Low-AoI data collection for multi-UAVs-UGVs assisted large-scale IoT systems based on workload balancing","authors":"Chang Deng , Xiuwen Fu , Savaglio Claudio , Giancarlo Fortino","doi":"10.1016/j.adhoc.2025.103844","DOIUrl":"10.1016/j.adhoc.2025.103844","url":null,"abstract":"<div><div>Unmanned Ground Vehicles (UGVs), due to their mobility and high power capacity, can serve as mobile base stations to assist Internet of Things (IoT) systems in remote areas lacking infrastructure for data collection. However, the slow speed of UGVs leads to significant transmission latency in large-scale IoT systems. Unmanned Aerial Vehicles (UAVs) offer advantages in terms of rapid mobility and flexibility. By deploying UAVs carried by UGVs to collaboratively perform data collection tasks, we can effectively enhance the performance of data collection. We refer to this system as an integrated UGV-UAV-assisted IoT system. In this system, multiple UGVs and UAVs are deployed to collect data from sensor nodes (SNs) over large areas. It is essential to consider the task regions assigned to each UGV and the UAVs they carry. UGVs equipped with more UAVs should handle data collection tasks for a greater number of SNs. To address this issue, we propose a low-latency data collection scheme for multi-UGVs-UAVs based on workload balancing (LMUWB). This scheme allocates appropriate task regions to each UGV based on the deployment locations of ground SNs and assigns an adequate number of UAVs according to the workload of each region. Additionally, deep reinforcement learning (DRL) is introduced to optimize the trajectories of UGVs and UAVs, enabling to reduce the system Age of Information (AoI), so as to ensure data freshness. Simulation experiments demonstrate that the LMUWB scheme can provide an effective solution for timely data collection in large-scale IoT systems.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"174 ","pages":"Article 103844"},"PeriodicalIF":4.4,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ad Hoc NetworksPub Date : 2025-04-03DOI: 10.1016/j.adhoc.2025.103842
Laxmi Chandolia , Pardeep Singh , Om Pal , Mohammed Misbahuddin , Vinod Kumar , Ram Prakash
{"title":"Authentication and security challenges for Unmanned Aerial Vehicles: A survey","authors":"Laxmi Chandolia , Pardeep Singh , Om Pal , Mohammed Misbahuddin , Vinod Kumar , Ram Prakash","doi":"10.1016/j.adhoc.2025.103842","DOIUrl":"10.1016/j.adhoc.2025.103842","url":null,"abstract":"<div><div>Unmanned Aerial Vehicles, commonly called drones, have gained significant interest worldwide, as these are mobile autonomous systems, and they have found applications in nearly every field. The rapid growth rate of drone use has exposed tremendous security concerns related to communication platforms, and authentication has become essential to ensure that data interchange between drones is safe. Traditional drones rely on established communication protocols, making them vulnerable to new threats emerging with the advent of a quantum-based world. The current literature still needs comprehensive authentication mechanisms for classical and quantum drones. This survey comprehensively reviews the critical differences in communication security between classical and quantum drones. The work addresses both paradigms’ needs, challenges, and constraints, making the requirement for strong authentication mechanisms essential. In addition, a comprehensive review of typical security threats, attacks, and relevant countermeasures is also provided on classical and quantum drones. Performance analysis computation and communication overhead comparisons are also performed to determine and compare authentication techniques. This work is essential for researchers and practitioners trying to develop security in the emerging landscape of drone technology because it bridges the gap that separates the classical from the quantum communication security of drones.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"174 ","pages":"Article 103842"},"PeriodicalIF":4.4,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ad Hoc NetworksPub Date : 2025-03-31DOI: 10.1016/j.adhoc.2025.103841
Zhendong Wang , Yaozhong Yang , Xiao Luo , Daojing He , Chan Sammy
{"title":"Energy efficient clustering and routing for wireless sensor networks by applying a spider wasp optimizer","authors":"Zhendong Wang , Yaozhong Yang , Xiao Luo , Daojing He , Chan Sammy","doi":"10.1016/j.adhoc.2025.103841","DOIUrl":"10.1016/j.adhoc.2025.103841","url":null,"abstract":"<div><div>In wireless sensor networks, the network lifespan is a key factor in evaluating the effectiveness of a routing protocol. Most traditional routing protocols optimize cluster head election and intercluster routing as separate phases, which limits improvements in intercluster routing optimization. To address this issue, we propose a multi-hop routing protocol based on the Spider Wasp Optimizer (SWO) algorithm. This protocol integrates cluster head election and intercluster routing in the cluster head selection phase, using the SWO algorithm for optimization. Many multi-hop routing protocols select the shortest total path for data transmission between clusters. However, this approach can result in the distance between two cluster heads exceeding a predefined threshold, leading to increased energy consumption during transmission. To mitigate this, we introduce a communication distance factor in the objective function for optimization, employing intermediate relay points to avoid long-distance transmissions. Specifically, we propose a central relay point strategy to minimize forwarding energy consumption. To address the issue of forwarding load optimization, we utilize K-means clustering to group cluster heads and combine this with equidistant relay points and the Dijkstra algorithm to identify the optimal multi-hop paths between clusters, thereby extending the network’s lifespan. The proposed routing algorithm is implemented in MATLAB and compared with the PSO-C, EECHS-ISSADE, HBACS, and SSA-FND protocols. In the simulated scenarios, the network lifespan was improved by up to 32.7%, 27.5%, 18.2%, and 9.2%, respectively.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"174 ","pages":"Article 103841"},"PeriodicalIF":4.4,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143807422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IoT-CAD: A comprehensive Digital Forensics dataset for AI-based Cyberattack Attribution Detection methods in IoT environments","authors":"Hania Mohamed , Nickolaos Koroniotis , Francesco Schiliro , Nour Moustafa","doi":"10.1016/j.adhoc.2025.103840","DOIUrl":"10.1016/j.adhoc.2025.103840","url":null,"abstract":"<div><div>Tracing and identifying attack characteristics, known as Cyberattack Attribution Detection (CAD), is in its early stages. It requires utilizing Deep Learning (DL) techniques to scan multiple devices to identify cyberattacks and detect their attributes effectively in IoT environments. Training and validation of these techniques require comprehensive datasets generated from heterogeneous data sources. However, there is a lack of high-quality and diverse IoT-based datasets involving cyberattack attributes. In this paper, a testbed and novel Internet of Things (IoT) forensics dataset suitable for CAD, called IoT-CAD, are introduced. The proposed dataset focuses on obtaining traces from Windows and Linux operating systems to encompass a plethora of sources, such as memory information, hard drives, processes, system calls, and network traffic. It incorporates traces from many IoT devices and realistic attack scenarios to ensure its relevance and applicability to real-world situations. After collecting, processing and analyzing the dataset, it is evaluated using Machine Learning (ML), Digital Forensics (DF), and Explainable AI (X-AI) techniques. The learning evaluation involves two approaches: Centralized learning for cyberattack detection; and Federated Learning (FL) for CAD. Also, network forensics is employed to investigate the network traffic to ensure that the dataset is realistic and accurately represents attack scenarios. Furthermore, X-AI techniques are used to assess the impact and contribution of each feature on the performances of the ML models, thus justifying the data features presented . This work can be considered a baseline for CAD methods in IoT environments. The dataset can be downloaded from <span><span>https://shorturl.at/zLDG6</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"174 ","pages":"Article 103840"},"PeriodicalIF":4.4,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}
Ad Hoc NetworksPub Date : 2025-03-31DOI: 10.1016/j.adhoc.2025.103843
Mehdi Zirak, Yasser Sedaghat, Mohammad Hossein Yaghmaee Moghaddam
{"title":"RPL-TSCH cross-layer design for improve quality of service in LLNs of IIoT","authors":"Mehdi Zirak, Yasser Sedaghat, Mohammad Hossein Yaghmaee Moghaddam","doi":"10.1016/j.adhoc.2025.103843","DOIUrl":"10.1016/j.adhoc.2025.103843","url":null,"abstract":"<div><div>The Internet of Things (IoT) facilitates mutual interaction by establishing a connection between humans and objects. The adoption of IoT is rapidly expanding across various aspects of human life. Industrial IoT (IIoT) is the intersection point between IoT and industry, serving as a key driver of the Fourth Industrial Revolution, also referred to as Industry 4.0 (I4.0). Low-Power and Lossy Networks (LLNs), which contain many resource-constrained nodes, as the basic block in IoT and IIoT, are an essential part of this revolution. Given the resource constraint of LLNs and the mission, safety, and business criticality of IIoT, enhancing Quality of Service (QoS) has become a significant challenge. Addressing this challenge requires the optimal utilization of resources and fully coordinated decision-making across different layer protocols, which can be achieved through cross-layer design. Routing Protocol for Low-Power and Lossy Networks (RPL) and Time Slotted Channel Hopping (TSCH) are two widely used standard protocols in the IIoT protocol stack. In this paper, we investigate the fundamental factors affecting QoS within the RPL and TSCH and propose an RPL-TSCH Cross-Layer (RTCL) design for LLNs in IIoT, motivated by equations derived from queuing theory. The equations and simulation results reveal that the inconsistency between the arrival rate and service rate of the node's queue leads to increasing <em>queue overflow</em> and delay and decreasing reliability and throughput. The proposed RTCL design, structured as a six-step solution that integrates RPL and TSCH information, enhances QoS by employing two primary strategies: <em>controlling the arrival rate</em> and <em>increasing the service rate</em> of the nodes’ queues. Evaluation results from various simulation scenarios demonstrate that RTCL improves QoS parameters while also enhancing load balancing and network stability.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"174 ","pages":"Article 103843"},"PeriodicalIF":4.4,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ad Hoc NetworksPub Date : 2025-03-28DOI: 10.1016/j.adhoc.2025.103839
Zhaowei Hu, Shiyun Ni, Hangyi Quan, Bocheng Ding, Peng He
{"title":"KAIM: A distributed K-anonymity selection mechanism based on dual incentives","authors":"Zhaowei Hu, Shiyun Ni, Hangyi Quan, Bocheng Ding, Peng He","doi":"10.1016/j.adhoc.2025.103839","DOIUrl":"10.1016/j.adhoc.2025.103839","url":null,"abstract":"<div><div>With the growing demand for privacy protection, the construction of anonymous zones based on distributed K-anonymity mechanisms has gained widespread attention in the field of location privacy protection. However, existing methods often overlook the limitations of reputation evaluation in identifying potential unknown malicious behaviors of collaborators when selecting assistants to build K-anonymous zones. At the same time, the issue of delayed responses from collaborators during the process of encouraging user cooperation through incentive mechanisms, which may lead to construction failures, has not been effectively addressed. To tackle these challenges, this paper proposes a dual-incentive distributed K-anonymity selection mechanism (KAIM) that combines the Hidden Markov Model (HMM). This mechanism encourages collaborators to participate in the construction of anonymous zones quickly and on time by establishing two incentive models: the requester collaboration incentive model and the collective benefit optimization incentive model. These dual incentives help form the optimal requester-collaborator participation set, enabling efficient construction of K-anonymous zones. Additionally, the KAIM mechanism uses the HMM to model the behaviors of requesters and collaborators, and its effectiveness in identifying malicious user behaviors is validated on real datasets. Experimental results show that the HMM model can identify anomalous activities that significantly differ from normal behavioral patterns with high accuracy, providing strong assurance for the construction of anonymous zones.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"175 ","pages":"Article 103839"},"PeriodicalIF":4.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143873395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}