Ad Hoc Networks最新文献_第2页

Gauss-AUKF based UWB/IMU fusion localization approach 基于Gauss-AUKF的UWB/IMU融合定位方法

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2025-04-13 DOI: 10.1016/j.adhoc.2025.103855

Mingsheng Wei , Lide Liu , Shidang Li , Di Wang , Wenshuai Li

{"title":"Gauss-AUKF based UWB/IMU fusion localization approach","authors":"Mingsheng Wei , Lide Liu , Shidang Li , Di Wang , Wenshuai Li","doi":"10.1016/j.adhoc.2025.103855","DOIUrl":"10.1016/j.adhoc.2025.103855","url":null,"abstract":"<div><div>To address the challenge of accurate positioning for ultra-wideband (UWB) systems in complex environments, this paper proposes a multi-sensor fusion localization method based on Gaussian-Adaptive Unscented Kalman Filtering (Gauss-AUKF) for UWB/IMU integration. The method rejects extreme values by performing Gaussian filtering optimization processing on the UWB range information to suppress the range error. And the UWB ranging information is fused with the data acquired by the inertial measurement unit (IMU) using an adaptive Unscented Kalman filter.An adaptive factor is introduced in the fusion process to minimize systematic errors and filter divergence by updating the measure noise covariance matrix in a real-time manner. The proposed method is validated through numerical simulations and experimental tests on a mobile robot equipped with a UWB hardware platform. The performance is evaluated in line-of-sight (LOS) and non-line-of-sight (NLOS) UWB scenarios, and compared with the traditional Extended Kalman Filter (EKF) , the Unscented Kalman Filter (UKF). The results demonstrate that the proposed approach significantly enhances localization accuracy in both LOS and NLOS conditions. The algorithm proposed in this paper has good performance in all three different NLOS environments.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"175 ","pages":"Article 103855"},"PeriodicalIF":4.4,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838534","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}

引用次数: 0

Double DQN-based Efficient Quality of Service Routing protocol in Internet of Underwater Things with mobile nodes 基于双dqn的水下物联网移动节点高效服务质量路由协议

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2025-04-12 DOI: 10.1016/j.adhoc.2025.103856

Meiyan Zhang , Yibo Liu , Hao Chen , Wenyu Cai

{"title":"Double DQN-based Efficient Quality of Service Routing protocol in Internet of Underwater Things with mobile nodes","authors":"Meiyan Zhang , Yibo Liu , Hao Chen , Wenyu Cai","doi":"10.1016/j.adhoc.2025.103856","DOIUrl":"10.1016/j.adhoc.2025.103856","url":null,"abstract":"<div><div>Internet of Underwater Things (IoUT) refers to a self-organizing network comprised of energy limited sensor nodes to collect underwater sensory information, which has become a popular research topic due to its both military and commercial applications. How to transmit sensory data to sink nodes with wireless acoustic communication is a great challenge to Internet of Underwater Things. This paper proposes a Double deep <span><math><mi>Q</mi></math></span> Network-based Efficient Quality of Service Routing protocol (DQN-EQSR in short) as the routing strategy of IoUT, which can improve transmission performance of wireless data delivery in IoUT. First of all, this paper establishes a wireless routing system for IoUT, where the applied Quality of Service (QoS) metric consists of packet delivery ratio, network life cycle, and end-to-end delay. Then, this paper establishes multi-dimensional state, multi-dimensional action, and multi-factor reward function for each sensor node. The multi-dimensional state includes node information and packet information, multi-dimensional action includes relay nodes selection and acoustic communication mode, and multi-factor reward function includes many factors such as energy cost, link quality cost, delay cost and packet priority. Moreover, a double Deep <span><math><mi>Q</mi></math></span> Network (DQN) is provided to evaluate the action value of nodes, where DQN1 is used to determine relay nodes, and DQN2 is used to determine acoustic communication controls. In addition, this paper conducts many simulations to prove the effectiveness of DQN-EQSR algorithm. Extensive simulation results show that the proposed DQN-EQSR algorithm outperforms other protocols in terms of packet forwarding hops, alive nodes ratio, residual energy ratio, average end-to-end delay and packet delivery ratio.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"175 ","pages":"Article 103856"},"PeriodicalIF":4.4,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838533","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}

引用次数: 0

A systematic literature review on spectrum detection for Cognitive Radio-Internet of Things networks 认知无线电-物联网网络频谱检测的系统文献综述

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2025-04-12 DOI: 10.1016/j.adhoc.2025.103857

Khadija Lahrouni , Hayat Semlali , Guillaume Andrieux , Jean-François Diouris , Abdelilah Ghammaz

{"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}

引用次数: 0

DTKD-IDS: A dual-teacher knowledge distillation intrusion detection model for the industrial internet of things DTKD-IDS：工业物联网双教师知识蒸馏入侵检测模型

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2025-04-11 DOI: 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}

引用次数: 0

An adaptive trust threshold based on Q-Learning for detecting intelligent attacks in vehicular Ad-Hoc Networks 基于q学习的自适应信任阈值检测车载Ad-Hoc网络中的智能攻击

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2025-04-09 DOI: 10.1016/j.adhoc.2025.103865

Xiao Liu , Li Liang , Zhencai Tan , Jining Chen , Gaoxiang Li

引用次数: 0

Real-time task dispatching and scheduling in serverless edge computing 无服务器边缘计算中的实时任务派遣和调度

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2025-04-09 DOI: 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}

引用次数: 0

Low-AoI data collection for multi-UAVs-UGVs assisted large-scale IoT systems based on workload balancing 基于工作负载平衡的多无人机- ugv低aoi数据收集辅助大规模物联网系统

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2025-04-05 DOI: 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}

引用次数: 0

Authentication and security challenges for Unmanned Aerial Vehicles: A survey 无人驾驶飞行器的认证和安全挑战：调查

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2025-04-03 DOI: 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}

引用次数: 0

Energy efficient clustering and routing for wireless sensor networks by applying a spider wasp optimizer 应用黄蜂优化器实现无线传感器网络的节能聚类和路由

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2025-03-31 DOI: 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}

引用次数: 0

IoT-CAD: A comprehensive Digital Forensics dataset for AI-based Cyberattack Attribution Detection methods in IoT environments IoT- cad：一个全面的数字取证数据集，用于物联网环境中基于ai的网络攻击归因检测方法

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2025-03-31 DOI: 10.1016/j.adhoc.2025.103840

Hania Mohamed , Nickolaos Koroniotis , Francesco Schiliro , Nour Moustafa

{"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}

引用次数: 0