Muhammad Shaheer¹, Feng Zeng^1,*, Aqsa Yasmeen², Mudasir Ahmad Wani^3,*, Kashish Ara Shakil⁴, Muhammad Asim⁵

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079701 - 08 May 2026

Abstract Malware remains a persistent and evolving threat to digital security, highlighting the need for advanced and resilient detection frameworks capable of mitigating increasingly sophisticated and evasive cyberattacks. Although deep learning ensembles have been explored, many existing approaches fail to balance computational efficiency with the diverse feature extraction capabilities needed for complex variants. To address this gap, this study proposes a novel stacking ensemble framework, MalDetect-IoT, which specifically eliminates the requirement for manual feature engineering and domain specific preprocessing traditionally required in malware classification. By fine-tuning two pre-trained models MobileNetV3 for its lightweight efficiency and Xception… More >

Kelan Wang¹, Jianfei Chen^2,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079644 - 08 May 2026

Abstract As 6G-enabled Industrial Internet of Things (IIoT) evolves, green and sustainable industrial monitoring increasingly relies on edge AI to deliver low-latency diagnosis under tight resource constraints. Industrial cyber–physical systems increasingly rely on heterogeneous sensing and communication infrastructures, where network-side attacks can propagate into physical processes and appear as coupled anomalies. Reliable diagnosis therefore requires joint learning from time-synchronized cyber and physical telemetry rather than modeling them as independent signals. This paper develops Cyber–Physical Symbiosis Network (CPSNet), a model designed for edge-AI deployment with a dual-stream architecture for fixed-window multiclass cross-domain anomaly diagnosis in IIoT. CPSNet… More >

Salahuddin¹, Khalid Haseeb^1,*, Mansoor Nasir¹, NZ Jhanjhi², Mamoona Humayun³

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079584 - 08 May 2026

Abstract Intelligent Transportation System (ITS) interconnects smart technologies for the advancement in communication and autonomous decision making in vehicle interactions. It manages traffic control infrastructure, analyses road conditions, and supports cooperative awareness in a crucial environment. The sensors continuously collect real-time vehicle data, process it, and forward it to analysis servers to predict the behavior of Vehicular Ad hoc Networks (VANETs). Many approaches have been proposed to address research challenges in routing and improve communication for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) systems. However, due to dynamic topology, the network becomes disturbed and loses established connections, leading… More >

Qingyao Gu^1,2,#, Mengqi Hu^2,#, Zerui Zhao², Liquan Chen^2,*, Huiyu Fang²

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.078873 - 08 May 2026

Abstract With the rapid development of the Internet of Things (IoT), the widespread adoption of applications such as smart homes and industrial IoT has raised the demand for secure authentication and key agreement among resource-constrained devices over open communication channels. Traditional authentication protocols often rely on centralized servers for key distribution, which results in high communication overhead and exposes systems to single-point-of-failure risks. Moreover, IoT devices are typically constrained in computational resources and are vulnerable to hardware cloning. These limitations necessitate lightweight yet robust security mechanisms. To address these challenges, we propose a lightweight peer-to-peer authentication More >

Afzal Badshah^1,*, Mona Eisa², Omar Alghushairy², Riad Alharbey², Manal Linjawi³, Ali Daud^4,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.077465 - 08 May 2026

Abstract The Internet of Things (IoT) devices generate massive data that leads to network congestion, propagation delays, and suboptimal resource allocation. Traditional Cloud Computing (CC) offers scalable resources required for that data; however, it has a long delay and communication overhead. On the other hand, Edge Computing (EC) guarantees low latency but has limited computational capacity. In this paper, we propose an intermediate paradigm, Regional Computing (RC), combined with a Fuzzy Logic System (FLS) for dynamic, multi-criteria offloading across edge, regional, and cloud. The FLS takes task size, cost, and computational demand as input metrics. It More >

Nader Karmous¹, Leila Bousbia¹, Mohamed Ould-Elhassen Aoueileyine¹, Imen Filali^2,*, Ridha Bouallegue¹

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.077454 - 08 May 2026

Abstract This study proposes an intelligent Intrusion Detection and Prevention System (IDPS) integrated into a centralized Ryu Software-Defined Networking (SDN) controller to mitigate replay attacks within Internet of Things (IoT) environments. To address the scarcity of specialized datasets, a comprehensive dataset was generated using a real-time SDN-IoT testbed encompassing Mininet, multiple OpenFlow 1.3 switches, and a single Ryu controller. The experimental setup featured the exchange of legitimate and malicious Message Queuing Telemetry Transport (MQTT) traffic between hosts and IoT devices to simulate realistic network behaviors and attack vectors. Our methodology introduces a novel feature engineering framework… More >

Anil Kumar¹, Abhay Bhatia¹, Amit Singh², Preeti Rani^3,*, Vincent Omollo Nyangaresi^4,*, Mahendihasan S. Heera⁵

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.076553 - 08 May 2026

Abstract The Internet of Things (IoT) enables seamless real-time monitoring and data exchange across distributed and heterogeneous environments with wireless sensor networks (WSNs). The open architecture and resource constraints of wireless sensor networks (WSNs) make them highly vulnerable to internal security threats caused by malicious or compromised nodes, particularly in Internet of Things (IoT) environments. To address this issue, we proposed Dynamic Trust Evaluation Model (DTEM), designed to provide a secure, scalable, and efficient framework for IoT-based WSNs. The proposed model identifies the role of trust management in routing, data aggregation, and intrusion detection, including trust-based… More >

Oluwatosin Ahmed Amodu¹, Zurina Mohd Hanapi^1,*, Raja Azlina Raja Mahmood¹, Faten A. Saif², Huda Althumali³, Chedia Jarray⁴, Umar Ali Bukar⁵, Mohammed Sani Adam⁶

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.074678 - 08 May 2026

Abstract Non-terrestrial networks (NTNs), encompassing unmanned aerial vehicles (UAVs), low-/high-altitude platforms (LAPs/HAPs), and satellite systems, are increasingly enabling Internet of Things (IoT) applications beyond the limits of terrestrial infrastructure. By combining UAV mobility with satellite and HAP coverage, NTN-assisted IoT supports diverse use cases, including remote sensing, smart cities, intelligent transportation, and emergency response. This paper presents a systematic mapping of machine learning (ML) research in NTN-assisted IoT with a focus on security-related aspects. A keyword co-occurrence analysis of over 2000 publications identifies twelve thematic clusters, including three clusters directly related to security, privacy, and trust.… More >

Reshma Siyal¹, Jun Long^1,*, Muhammad Asim^2,*, Mudasir Ahmad Wani³, Kashish Ara Shakil⁴, Sajid Shah²

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.074282 - 08 May 2026

Abstract The rapid growth of the Internet of Things (IoT) has led to dense wireless sensor networks (WSNs) deployed in critical applications such as smart cities, industrial monitoring, and healthcare. However, energy constraints, unpredictable communication delays, and inefficient data aggregation remain significant challenges that limit network reliability and operational lifespan. Traditional approaches often fail to balance delay minimization with energy efficiency, especially in large-scale or dynamic networks. To address these issues, this study proposes CTSO-DRNN, a novel framework that integrates Chronological Tangent Search Optimization (CTSO) with a Deep Recurrent Neural Network (DRNN) for accurate delay prediction… More >

Jaekyung Lee^1,2, Youngjun Kim², Byungsung Ko², Taewon Kim², Jaeheon Park², Jiwon Lee², Wonhee Kim^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.080624 - 27 April 2026

Abstract Automated reading of analog gauges in industrial environments is essential for predictive maintenance and safety monitoring. However, conventional computer vision approaches encounter two fundamental bottlenecks: polar unwrapping techniques induce severe nonlinear scaling distortions under oblique viewing angles and axis-aligned bounding boxes (AABBs) are geometrically inefficient for encapsulating high-aspect-ratio rotating needles. To overcome these limitations, this paper proposes a novel end-to-end framework that innovatively redefines gauge reading as a structural pose estimation task. We model each gauge as a topological five-keypoint skeleton (kstart,kmid,kcenter,kend,ktip), and localize these landmarks using a customized P2-YOLO-Pose architecture. By integrating a high-resolution… More >