Kyoungmin Roh¹, Seungmin Lee², Seong-je Cho^2,*, Youngsup Hwang³, Dongjae Kim⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2026.074936 - 30 March 2026

Abstract Many machine learning–based Android malware detection often suffers from concept drift, where models trained on historical data fail to generalize to evolving threats. This paper proposes SCAN (Structural Clustering with Adaptive thresholds for iNtelligent Android malware detection), a hybrid intelligent framework designed to mitigate concept drift without retraining. SCAN integrates Gaussian Mixture Models (GMMs)-based clustering with cluster-wise adaptive thresholding and supervised classifiers tailored to each cluster. A key challenge in clustering-based malware detection is cluster-wise class imbalance, where clusters contain disproportionate distributions of benign and malicious samples. SCAN addresses this issue through adaptive thresholding, which dynamically… More >

Heesoo Kim¹, Minwook Kim¹, Hyorim Han², Soongbong Lee², Tai-jin Song^1,*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.074802 - 12 March 2026

Abstract Autonomous vehicles operate without direct human intervention, which introduces safety risks that differ from those of conventional vehicles. Although many studies have examined safety issues related to autonomous driving, high-risk situations have often been defined using single indicators, making it difficult to capture the complex and evolving nature of accident risk. To address this limitation, this study proposes a structured framework for defining and analyzing high-risk situations throughout the traffic accident process. High-risk situations are described using three complementary indicators: accident likelihood, accident severity, and accident duration. These indicators explain how risk emerges, increases, and… More >

Sabina-Cristiana Necula^*, Napoleon-Alexandru Sireteanu

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-34, 2026, DOI:10.32604/cmc.2025.070861 - 09 December 2025

Abstract Modern business information systems face significant challenges in managing heterogeneous data sources, integrating disparate systems, and providing real-time decision support in complex enterprise environments. Contemporary enterprises typically operate 200+ interconnected systems, with research indicating that 52% of organizations manage three or more enterprise content management systems, creating information silos that reduce operational efficiency by up to 35%. While attention mechanisms have demonstrated remarkable success in natural language processing and computer vision, their systematic application to business information systems remains largely unexplored. This paper presents the theoretical foundation for a Hierarchical Attention-Based Business Information System (HABIS)… More >

Puneetha B. H.^1,*, Manoj Kumar M. V.^2,*, Prashanth B. S.², Piyush Kumar Pareek³

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-33, 2026, DOI:10.32604/cmc.2025.067706 - 10 November 2025

Abstract Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational, organizational, or regulatory factors. These changes, referred to as incremental concept drift, gradually alter the behavior or structure of processes, making their detection and localization a challenging task. Traditional process mining techniques frequently assume process stationarity and are limited in their ability to detect such drift, particularly from a control-flow perspective. The objective of this research is to develop an interpretable and robust framework capable of detecting and localizing incremental concept drift in event logs, with a… More >

Soumia Zertal^1,2,*, Asma Saighi^1,2, Sofia Kouah^1,2, Souham Meshoul^3,*, Zakaria Laboudi^2,4

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3737-3782, 2025, DOI:10.32604/cmes.2025.068558 - 30 September 2025

Abstract Cardiovascular diseases (CVDs) continue to present a leading cause of mortality worldwide, emphasizing the importance of early and accurate prediction. Electrocardiogram (ECG) signals, central to cardiac monitoring, have increasingly been integrated with Deep Learning (DL) for real-time prediction of CVDs. However, DL models are prone to performance degradation due to concept drift and to catastrophic forgetting. To address this issue, we propose a real-time CVDs prediction approach, referred to as ADWIN-GFR that combines Convolutional Neural Network (CNN) layers, for spatial feature extraction, with Gated Recurrent Units (GRU), for temporal modeling, alongside adaptive drift detection and… More > Graphic Abstract

Kagiso Komane^1,*, Lucas Khoza², Fani Radebe¹

Journal of Cyber Security, Vol.7, pp. 79-108, 2025, DOI:10.32604/jcs.2025.059712 - 20 May 2025

Abstract Financial support, government support, cyber hygiene, and ongoing education and training as well as parental guidance and supervision are all essential components of cybersecurity awareness (CSA) identified in this study among the youth. It’s critical to realize that adequate funding is needed to effectively increase CSA, particularly among South African youth. Previous studies have demonstrated several ways to address inadequate CSA by utilizing various cybersecurity frameworks, ideas, and models. To increase CSA, this literature review seeks to emphasize the significance of integrating cybersecurity education throughout the entire school curriculum. This paper identified ethical issues, protection… More >

Jianlong Wang^1,#, Xiumei Chen^1,2,#, Muqi Huang³, Rui Liu³, I-Hua Chen^4,5,*, Gordon L. Flett^6,*

International Journal of Mental Health Promotion, Vol.27, No.2, pp. 241-256, 2025, DOI:10.32604/ijmhp.2025.058503 - 03 March 2025

Abstract Background: This study addresses the pressing need to understand the nuanced relationship between ‘mattering’—the perception of being significant to others—and problematic internet use (PIU) among university students. Unlike previous research that has primarily employed variable-centered approaches, this study first adopts a person-centered approach using Latent Profile Analysis (LPA) to identify distinct mattering profiles. Subsequently, through variable-centered analyses, these profiles are examined in relation to different types of PIU—specifically problematic social media use (PSMU) and problematic gaming (PG)—as well as adaptability. Methods: Data were collected from 3587 university students across 19 universities in China. Participants completed… More >

Yongjun Ren¹, Zhiming Wang¹, Pradip Kumar Sharma², Fayez Alqahtani³, Amr Tolba⁴, Jin Wang^5,*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 1593-1613, 2025, DOI:10.32604/cmc.2025.059170 - 17 February 2025

Abstract In the context of an increasingly severe cybersecurity landscape and the growing complexity of offensive and defensive techniques, Zero Trust Networks (ZTN) have emerged as a widely recognized technology. Zero Trust not only addresses the shortcomings of traditional perimeter security models but also consistently follows the fundamental principle of “never trust, always verify.” Initially proposed by John Cortez in 2010 and subsequently promoted by Google, the Zero Trust model has become a key approach to addressing the ever-growing security threats in complex network environments. This paper systematically compares the current mainstream cybersecurity models, thoroughly explores More >

Dawei Xu^1,2,3, Min Wang¹, Yue Lv¹, Moxuan Fu², Yi Wu^4,5,*, Jian Zhao¹

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2027-2041, 2025, DOI:10.32604/cmc.2024.058178 - 17 February 2025

Abstract Website fingerprinting (WF) attacks can reveal information about the websites users browse by de-anonymizing encrypted traffic. Traditional website fingerprinting attack models, focusing solely on a single spatial feature, are inefficient regarding training time. When confronted with the concept drift problem, they suffer from a sharp drop in attack accuracy within a short period due to their reliance on extensive, outdated training data. To address the above problems, this paper proposes a parallel website fingerprinting attack (APWF) that incorporates an attention mechanism, which consists of an attack model and a fine-tuning method. Among them, the APWF… More >

Dexian Li¹, Wencan Li², Xin Lin^3,*, Xingchen Zhu^4,*

International Journal of Mental Health Promotion, Vol.27, No.1, pp. 1-17, 2025, DOI:10.32604/ijmhp.2024.058744 - 31 January 2025

Abstract Background: The phenomenon of academic anxiety has been demonstrated to exert a considerable influence on students’ academic engagement, leading to the emergence of a phenomenon known as “learned helplessness” and undermining the self-confidence and motivation of high school students. Using acceptance-rejection theory, this study elucidated how a rejective parenting style affects Chinese high school students’ academic anxiety and explored the urban-rural heterogeneity of this relationship. Methods: Data were analyzed using a stratified whole-cluster random sampling method. There are a total of 30,000 high school students in the three regions of northern and central China (from… More >