Misbah Anwer^1,*, Ghufran Ahmed¹, Maha Abdelhaq², Raed Alsaqour³, Shahid Hussain⁴, Adnan Akhunzada^5,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-15, 2026, DOI:10.32604/cmc.2025.068673 - 10 November 2025

Abstract The exponential growth of the Internet of Things (IoT) has introduced significant security challenges, with zero-day attacks emerging as one of the most critical and challenging threats. Traditional Machine Learning (ML) and Deep Learning (DL) techniques have demonstrated promising early detection capabilities. However, their effectiveness is limited when handling the vast volumes of IoT-generated data due to scalability constraints, high computational costs, and the costly time-intensive process of data labeling. To address these challenges, this study proposes a Federated Learning (FL) framework that leverages collaborative and hybrid supervised learning to enhance cyber threat detection in… More >

Guangyu Xu^1,2, Siyuan Xu³, Siyu Lu^4,*, Yuxin Liu¹, Bo Yang¹, Junmin Lyu⁵, Wenfeng Zheng^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 4037-4053, 2025, DOI:10.32604/cmes.2025.074901 - 23 December 2025

Abstract Robust stereo disparity estimation plays a critical role in minimally invasive surgery, where dynamic soft tissues, specular reflections, and data scarcity pose major challenges to traditional end-to-end deep learning and deformable model-based methods. In this paper, we propose a novel disparity estimation framework that leverages a pretrained StyleGAN generator to represent the disparity manifold of Minimally Invasive Surgery (MIS) scenes and reformulates the stereo matching task as a latent-space optimization problem. Specifically, given a stereo pair, we search for the optimal latent vector in the intermediate latent space of StyleGAN, such that the photometric reconstruction… More >

Nader Karmous¹, Wadii Jlassi¹, Mohamed Ould-Elhassen Aoueileyine¹, Imen Filali^2,*, Ridha Bouallegue¹

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 4363-4393, 2025, DOI:10.32604/cmes.2025.074178 - 23 December 2025

Abstract This paper introduces a robust Distributed Denial-of-Service attack detection framework tailored for Software-Defined Networking based Internet of Things environments, built upon a novel, synthetic multi-vector dataset generated in a Mininet-Ryu testbed using real-time flow-based labeling. The proposed model is based on the XGBoost algorithm, optimized with Principal Component Analysis for dimensionality reduction, utilizing lightweight flow-level features extracted from OpenFlow statistics to classify attacks across critical IoT protocols including TCP, UDP, HTTP, MQTT, and CoAP. The model employs lightweight flow-level features extracted from OpenFlow statistics to ensure low computational overhead and fast processing. Performance was rigorously… More >

J. H. Azzawi^a, Yaseen A. Al-Zahraa^b, M. A. Abdulmajeed^c, K. A. Jasim^c, A. Muravitskaya^e, A. A. Al-Hamadani^d,e, A. H. Al-Dulaimi^d,e

Chalcogenide Letters, Vol.22, No.7, pp. 593-601, 2025, DOI:10.15251/CL.2025.227.593

Abstract Four Se₇₀Ge₂₀Sb₁₀ alloy samples were prepared using the melt quenching technique. To improve the energy states of the mobility gap, the samples were exposed to gamma radiation from 60Co source at various doses of 600, 1200, 1500, and 2000 Gy. The electrical characteristics were examined both before and after irradiation. The conductivity analysis revealed that all of our samples were impacted by gamma radiation. The reorganization of the amorphous lattice and the degree of radiation-induced disorder have been involved in the changes that occurred in the electrical characteristics of the irradiated samples. All irradiated and non-irradiated… More >

Bappa Muktar^*, Vincent Fono, Adama Nouboukpo

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4705-4727, 2025, DOI:10.32604/cmc.2025.067733 - 23 October 2025

Abstract Vehicular Ad Hoc Networks (VANETs) are central to Intelligent Transportation Systems (ITS), especially for real-time communication involving emergency vehicles. Yet, Distributed Denial of Service (DDoS) attacks can disrupt safety-critical channels and undermine reliability. This paper presents a robust, scalable framework for detecting DDoS attacks in highway VANETs. We construct a new dataset with Network Simulator 3 (NS-3) and Simulation of Urban Mobility (SUMO), enriched with real mobility traces from Germany’s A81 highway (OpenStreetMap). Three traffic classes are modeled: DDoS, Voice over IP (VoIP), and Transmission Control Protocol Based (TCP-based) video streaming (VideoTCP). The pipeline includes normalization,… More >

Seulki Han¹, Sangho Son², Won Sakong², Haemin Jung^3,*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2893-2912, 2025, DOI:10.32604/cmc.2025.067211 - 23 September 2025

Abstract As cyber threats become increasingly sophisticated, Distributed Denial-of-Service (DDoS) attacks continue to pose a serious threat to network infrastructure, often disrupting critical services through overwhelming traffic. Although unsupervised anomaly detection using convolutional autoencoders (CAEs) has gained attention for its ability to model normal network behavior without requiring labeled data, conventional CAEs struggle to effectively distinguish between normal and attack traffic due to over-generalized reconstructions and naive anomaly scoring. To address these limitations, we propose CA-CAE, a novel anomaly detection framework designed to improve DDoS detection through asymmetric joint reconstruction learning and refined anomaly scoring. Our… More >

Mohammad Nowsin Amin Sheikh^1,2,*, Muhammad Saibtain Raza¹, I-Shyan Hwang^1,*, Md. Alamgir Hossain³, Ihsan Ullah¹, Tahmid Hasan⁴, Mohammad Syuhaimi Ab-Rahman⁵

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 4043-4066, 2025, DOI:10.32604/cmc.2025.065850 - 23 September 2025

Abstract The rapid advancement of the Internet of Things (IoT) has heightened the importance of security, with a notable increase in Distributed Denial-of-Service (DDoS) attacks targeting IoT devices. Network security specialists face the challenge of producing systems to identify and offset these attacks. This research manages IoT security through the emerging Software-Defined Networking (SDN) standard by developing a unified framework (RNN-RYU). We thoroughly assess multiple deep learning frameworks, including Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Feed-Forward Convolutional Neural Network (FFCNN), and Recurrent Neural Network (RNN), and present the novel usage of Synthetic Minority Over-Sampling More >

Singamaneni Krishnapriya^1,2,*, Sukhvinder Singh¹

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1849-1881, 2025, DOI:10.32604/cmes.2025.068326 - 31 August 2025

Abstract The explosive expansion of the Internet of Things (IoT) systems has increased the imperative to have strong and robust solutions to cyber Security, especially to curtail Distributed Denial of Service (DDoS) attacks, which can cripple critical infrastructure. The proposed framework presented in the current paper is a new hybrid scheme that induces deep learning-based traffic classification and blockchain-enabled mitigation to make intelligent, decentralized, and real-time DDoS countermeasures in an IoT network. The proposed model fuses the extracted deep features with statistical features and trains them by using traditional machine-learning algorithms, which makes them more accurate… More > Graphic Abstract

Sumeyra Ucar¹, Muhammed Aldaif ², Esra Yaprak¹, Esma Yigider ², Murat Aydin^2,*, Emre Ilhan¹, Abdulkadir Ciltas², Ertan Yildirim³

Phyton-International Journal of Experimental Botany, Vol.94, No.8, pp. 2461-2477, 2025, DOI:10.32604/phyton.2025.068383 - 29 August 2025

Abstract Wheat is a crucial crop for global food security, and effective in vitro plant regeneration techniques are considered a precondition for genetic engineering in wheat breeding programs. A practical approach for in vitro regeneration of the Kırik bread wheat cultivar via somatic embryogenesis was investigated using endosperm-supported mature embryos. Callus cultures were initiated from mature embryos supported by endosperm, cultured on phytagel-based Murashige and Skoog (MS) basal medium containing dicamba (12 mg/L) and indole-3-acetic acid (IAA) (0.5 mg/L) under dark conditions. This research was designed to examine the impact of putrescine (Put) (0.0 and 1.0 mM) on… More >

Prasanalakshmi Balaji^1,2, Sangita Babu³, Maode Ma⁴, Zhaoxi Fang², Syarifah Bahiyah Rahayu^5,6,*, Mariyam Aysha Bivi¹, Mahaveerakannan Renganathan⁷

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5831-5858, 2025, DOI:10.32604/cmc.2025.065260 - 30 July 2025

Abstract The rapid progression of the Internet of Things (IoT) technology enables its application across various sectors. However, IoT devices typically acquire inadequate computing power and user interfaces, making them susceptible to security threats. One significant risk to cloud networks is Distributed Denial-of-Service (DoS) attacks, where attackers aim to overcome a target system with excessive data and requests. Among these, low-rate DoS (LR-DoS) attacks present a particular challenge to detection. By sending bursts of attacks at irregular intervals, LR-DoS significantly degrades the targeted system’s Quality of Service (QoS). The low-rate nature of these attacks confuses their… More >