Xinli Hao¹, Qingyuan Gong², Yang Chen^1,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073155 - 12 January 2026

Abstract Topological information is very important for understanding different types of online web services, in particular, for online social networks (OSNs). People leverage such information for various applications, such as social relationship modeling, community detection, user profiling, and user behavior prediction. However, the leak of such information will also pose severe challenges for user privacy preserving due to its usefulness in characterizing users. Large-scale web crawling-based information probing is a representative way for obtaining topological information of online web services. In this paper, we explore how to defend against topological information probing for online web services,… More >

Bello Musa Yakubu^1,*, Nor Shahida Mohd Jamail ², Rabia Latif ², Seemab Latif ³

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072426 - 12 January 2026

Abstract Federated Learning (FL) enables joint training over distributed devices without data exchange but is highly vulnerable to attacks by adversaries in the form of model poisoning and malicious update injection. This work proposes Secured-FL, a blockchain-based defensive framework that combines smart contract–based authentication, clustering-driven outlier elimination, and dynamic threshold adjustment to defend against adversarial attacks. The framework was implemented on a private Ethereum network with a Proof-of-Authority consensus algorithm to ensure tamper-resistant and auditable model updates. Large-scale simulation on the Cyber Data dataset, under up to 50% malicious client settings, demonstrates Secured-FL achieves 6%–12% higher accuracy, More >

Hongwei Wu^*, Guojian Li, Hanyun Zhang, Zi Ye, Chao Ma

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071008 - 12 January 2026

Abstract Federated Learning (FL) protects data privacy through a distributed training mechanism, yet its decentralized nature also introduces new security vulnerabilities. Backdoor attacks inject malicious triggers into the global model through compromised updates, posing significant threats to model integrity and becoming a key focus in FL security. Existing backdoor attack methods typically embed triggers directly into original images and consider only data heterogeneity, resulting in limited stealth and adaptability. To address the heterogeneity of malicious client devices, this paper proposes a novel backdoor attack method named Capability-Adaptive Shadow Backdoor Attack (CASBA). By incorporating measurements of clients’… More >

Jing Shan¹, Catherine King^2,3, Harunor Rashid^3,4, Veysel Kayser^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.070851 - 30 December 2025

Abstract Objectives: B-cell maturation antigen (BCMA)-targeted antibody–drug conjugates (ADCs) have emerged as promising therapies for relapsed/refractory multiple myeloma (RRMM), but the overall efficacy and safety profile is unclear. This study aimed to synthesize the available evidence on the safety and efficacy of BCMA-ADCs in development for RRMM. Methods: A systematic search was conducted using six bibliographic databases and ClinicalTrials.gov up to November 2024. Studies were eligible if they were human clinical trials or animal studies evaluating BCMA-ADCs and reported efficacy and safety outcomes. Data extraction and quality assessments were conducted using validated tools, including ROBINS-I… More >

Ran Wei^*, Hui Shu

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-23, 2026, DOI:10.32604/cmc.2025.069562 - 10 November 2025

Abstract Transformer-based models have significantly advanced binary code similarity detection (BCSD) by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings. Although adversarial examples can strategically undermine the accuracy of BCSD models and protect critical code, existing techniques predominantly depend on inserting artificial instructions, which incur high computational costs and offer limited diversity of perturbations. To address these limitations, we propose AIMA, a novel gradient-guided assembly instruction relocation method. Our method decouples the detection model into tokenization, embedding, and encoding layers to enable efficient gradient computation. Since token IDs of instructions are… More >

Hafida Khelafi¹, Wassima Lakhdari², Mustapha Mounir Bouhenna³, Said Boudeffeur⁴, Hayet Meamiche¹, Salah Neghmouche Nacer^5,*, Meriam Laouar⁶

Phyton-International Journal of Experimental Botany, Vol.94, No.12, pp. 3975-3989, 2025, DOI:10.32604/phyton.2025.073210 - 29 December 2025

Abstract Essential oils (EOs) derived from medicinal plants are gaining recognition as sustainable alternatives to synthetic fungicides in the management of plant pathogens. This study investigates the chemical composition, chromatographic profile, and antifungal of Mentha rotundifolia essential oil against Fusarium oxysporum f. sp. albedinis (Foa), the pathogen responsible for Bayoud disease in date palm. The oil was extracted through hydrodistillation and characterized using thin-layer chromatography (TLC) and gas chromatography–mass spectrometry (GC-MS), revealing multiple fractions corresponding to terpenoid constituents and 23 chemical constituents, predominantly oxygenated monoterpenes (68.51%), with piperitenone oxide as the major component (62.53%). The antifungal efficacy was evaluated… More >

Md Salah Uddin^*

Journal of Polymer Materials, Vol.42, No.4, pp. 1051-1073, 2025, DOI:10.32604/jpm.2025.070688 - 26 December 2025

Abstract Carbon fiber-reinforced composites (CFRCs) have a wide range of applications in the aerospace, automotive, and energy sectors. A higher specific strength-to-weight ratio is desired in high-performance applications. The failure mechanism of CFRCs involves multiscale phenomena, such as failure that can occur at the matrix, fibers, interface, layers, lamina, and laminates. When an impactor hits the CFRCs, the design involves analyzing each of these stages to prevent failure and optimize the properties of CFRCs under various loading conditions. A numerical model was employed to predict the fracture toughness of CFRCs with varying weight fractions and orientations.… More >

Rym Akrout¹, Ludovic Leloup², Khouloud Ayed¹, Fabrice Parat², Sami Zekri^3,4, Wassim Y. Almawi¹, Rahma Boughriba¹, Hanen Attia¹, Olfa Masmoudi-Kouki⁴, Hervé Kovacic^2,*, Asma Gati^1,*

Oncology Research, Vol.33, No.12, pp. 3887-3906, 2025, DOI:10.32604/or.2025.070729 - 27 November 2025

Abstract Objectives: Cisplatin (CDDP) therapy for glioblastoma (GBM) is linked with several limitations, which include poor penetration of the blood-brain barrier (BBB), systemic toxicity, and the development of drug resistance mechanisms implicating oxidative stress dysregulation and compromised apoptotic pathways. This study evaluates C-Phycocyanin (C-PC) as a potential adjuvant to enhance CDDP efficacy by modulating redox balance and apoptosis. Methods: GBM cells (U87 and U87-EGFRvIII) were treated with CDDP, C-PC, or their combination. Cell viability was assessed by MTT assay; apoptosis was evaluated by DAPI staining and Western blot analysis of cleaved Caspase-3 and poly (ADP-ribose) polymerase… More > Graphic Abstract

Seunghan Kim^1,#, Changhoon Lim^2,#, Gwonsang Ryu³, Hyunil Kim^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2617-2630, 2025, DOI:10.32604/cmes.2025.071190 - 26 November 2025

Abstract Federated Learning enables privacy-preserving training of Transformer-based language models, but remains vulnerable to backdoor attacks that compromise model reliability. This paper presents a comparative analysis of defense strategies against both classical and advanced backdoor attacks, evaluated across autoencoding and autoregressive models. Unlike prior studies, this work provides the first systematic comparison of perturbation-based, screening-based, and hybrid defenses in Transformer-based FL environments. Our results show that screening-based defenses consistently outperform perturbation-based ones, effectively neutralizing most attacks across architectures. However, this robustness comes with significant computational overhead, revealing a clear trade-off between security and efficiency. By explicitly More >

Sahbi Boubaker^1,2,*, Salim Hadj Said³, Souad Kamel¹, Habib Dimassi³

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5703-5721, 2025, DOI:10.32604/cmc.2025.069047 - 23 October 2025

Abstract Accurate trajectory tracking in lower-limb exoskeletons is challenged by the nonlinear, time-varying dynamics of human-robot interaction, limited sensor availability, and unknown external disturbances. This study proposes a novel control strategy that combines flatness-based control with two cascaded observers: a high-gain observer to estimate unmeasured joint velocities, and a nonlinear disturbance observer to reconstruct external torque disturbances in real time. These estimates are integrated into the control law to enable robust, state-feedback-based trajectory tracking. The approach is validated through simulation scenarios involving partial state measurements and abrupt external torque perturbations, reflecting realistic rehabilitation conditions. Results confirm More >