Dong-Hyuk Shin¹, Jae-Jun Ha¹, Ieck-Chae Euom^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3795-3838, 2025, DOI:10.32604/cmes.2025.066727 - 30 June 2025

Abstract The accelerated global adoption of electric vehicles (EVs) is driving significant expansion and increasing complexity within the EV charging infrastructure, consequently presenting novel and pressing cybersecurity challenges. While considerable effort has focused on preventative cybersecurity measures, a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents, a gap exacerbated by system heterogeneity, distributed digital evidence, and inconsistent logging practices which hinder effective incident reconstruction and attribution. This paper addresses this critical need by proposing a novel, data-driven forensic framework tailored to the EV charging infrastructure, focusing on the systematic identification, classification,… More >

Ammar Odeh^*, Anas Abu Taleb

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 447-461, 2025, DOI:10.32604/cmc.2025.065426 - 09 June 2025

Abstract The increasing deployment of Internet of Things (IoT) devices has introduced significant security challenges, including identity spoofing, unauthorized access, and data integrity breaches. Traditional security mechanisms rely on centralized frameworks that suffer from single points of failure, scalability issues, and inefficiencies in real-time security enforcement. To address these limitations, this study proposes the Blockchain-Enhanced Trust and Access Control for IoT Security (BETAC-IoT) model, which integrates blockchain technology, smart contracts, federated learning, and Merkle tree-based integrity verification to enhance IoT security. The proposed model eliminates reliance on centralized authentication by employing decentralized identity management, ensuring tamper-proof… More >

Lan Luo^1,2, Yangyang Zhan^1,2, Xinna Hu², Jingjie Zhou^1,2, Haibin Li^2,3,*

International Journal of Mental Health Promotion, Vol.27, No.4, pp. 541-559, 2025, DOI:10.32604/ijmhp.2025.061043 - 30 April 2025

Abstract Objectives: The prevalence of cyber-aggression is increasing worldwide, resulting in significant negative impacts on both perpetrators and victims. This study aimed to investigate the relationship between cyber-ostracism and cyber-aggression among college students, clarify the role of various types of rumination in this dynamic. Methods: A total of 1198 Chinese college students (67.4% female; mean age 20.78 years; SD = 1.12) were recruited through cluster random sampling and completed the Cyber-ostracism Experience Scale (COES), Positive and Negative Rumination Scale (PANRS), and Adolescent Online Aggression Behavior Scale (AOABS). The structural equation model (SEM) was employed to examine the… More >

Zubair Ashraf¹, Yasar Sajjad^1,*, Sabaz Ali Khan¹, Gulzar Akhtar², Ahmed Mahmoud Ismail^3,4,*, Tarek A. Shalaby³, Bader Alsubaie⁵, Othman Al-Dossary⁵

Phyton-International Journal of Experimental Botany, Vol.94, No.3, pp. 987-1006, 2025, DOI:10.32604/phyton.2025.062351 - 31 March 2025

Abstract The medicinal herb Geranium wallichianum belongs to the family Geraniaceae. The East Asian Himalayas are its primary habitat. Overexploitation and overharvesting pose a threat to this plant, given its extensive ethnomedical utilization in the community. In Pakistan, its population has already declined by over 75%. Given its critical medicinal importance, urgent conservation efforts are needed to prevent extinction. The aim of the current research was to determine the effectiveness of sucrose and polyethylene glycol (PEG) in decelerating the growth of this medicinally important species. Nodal segments were utilized as explant with varying levels of polyethylene glycol… More >

Mathew Nicho^1,2,*, Oluwasegun Adelaiye³, Christopher D. McDermott⁴, Shini Girija⁵

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 281-308, 2025, DOI:10.32604/cmc.2025.059597 - 26 March 2025

Abstract The successful penetration of government, corporate, and organizational IT systems by state and non-state actors deploying APT vectors continues at an alarming pace. Advanced Persistent Threat (APT) attacks continue to pose significant challenges for organizations despite technological advancements in artificial intelligence (AI)-based defense mechanisms. While AI has enhanced organizational capabilities for deterrence, detection, and mitigation of APTs, the global escalation in reported incidents, particularly those successfully penetrating critical government infrastructure has heightened concerns among information technology (IT) security administrators and decision-makers. Literature review has identified the stealthy lateral movement (LM) of malware within the initially… More >

Muhammad Armghan Latif¹, Zohaib Mushtaq^2,*, Saifur Rahman³, Saad Arif⁴, Salim Nasar Faraj Mursal³, Muhammad Irfan³, Haris Aziz⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1667-1695, 2025, DOI:10.32604/cmes.2024.056850 - 27 January 2025

Abstract Ransomware attacks pose a significant threat to critical infrastructures, demanding robust detection mechanisms. This study introduces a hybrid model that combines vision transformer (ViT) and one-dimensional convolutional neural network (1DCNN) architectures to enhance ransomware detection capabilities. Addressing common challenges in ransomware detection, particularly dataset class imbalance, the synthetic minority oversampling technique (SMOTE) is employed to generate synthetic samples for minority class, thereby improving detection accuracy. The integration of ViT and 1DCNN through feature fusion enables the model to capture both global contextual and local sequential features, resulting in comprehensive ransomware classification. Tested on the UNSW-NB15 More >

Hayatu Uma^1,*, Abdulaziz Aminu¹, Raghu Cherukupalli², Femi Akindotun Akintomide¹, Abdul Habu³, Aisha Aminu Lawal¹, Adamu Mohammad¹

Congenital Heart Disease, Vol.19, No.6, pp. 635-645, 2024, DOI:10.32604/chd.2025.056641 - 27 January 2025

Abstract Laubry-Pezzi syndrome (L-PS) is a rare congenital heart disease characterized by a ventricular septal defect (VSD) and aortic valve prolapse. These cardiac lesions predispose individuals to infective endocarditis (IE), a life-threatening complication, especially in resource-constrained settings. A 17-year-old male presented with a three-week history of fever and headache, and a one-week history of abdominal pain, vomiting, and diarrhea. On presentation, he appeared toxic, was febrile, tachypneic, tachycardic, and blood pressure of 120/30 mmHg, and heart sounds were S1, S2. Abdominal examination revealed generalized tenderness. A provisional diagnosis of typhoid sepsis with intestinal perforation was considered.… More >

Ammar Odeh^*, Anas Abu Taleb

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4149-4169, 2024, DOI:10.32604/cmc.2024.058052 - 19 December 2024

Abstract The proliferation of Internet of Things (IoT) technology has exponentially increased the number of devices interconnected over networks, thereby escalating the potential vectors for cybersecurity threats. In response, this study rigorously applies and evaluates deep learning models—namely Convolutional Neural Networks (CNN), Autoencoders, and Long Short-Term Memory (LSTM) networks—to engineer an advanced Intrusion Detection System (IDS) specifically designed for IoT environments. Utilizing the comprehensive UNSW-NB15 dataset, which encompasses 49 distinct features representing varied network traffic characteristics, our methodology focused on meticulous data preprocessing including cleaning, normalization, and strategic feature selection to enhance model performance. A robust… More >

Carlos Merlano^*

Journal of Cyber Security, Vol.6, pp. 89-116, 2024, DOI:10.32604/jcs.2024.056164 - 06 December 2024

Abstract The constantly increasing degree and frequency of cyber threats require the emergence of flexible and intelligent approaches to systems’ protection. Despite the calls for the use of artificial intelligence (AI) and machine learning (ML) in strengthening cyber security, there needs to be more literature on an integrated view of the application areas, open issues or trends in AI and ML for cyber security. Based on 90 studies, in the following literature review, the author categorizes and systematically analyzes the current research field to fill this gap. The review evidences that, in contrast to rigid rule-based… More >

Bojana Z. Jadranin¹, Marija V. Ćosić¹, Djordje P. Božović¹, Milorad M. Vujičić^1,2, Beáta Papp³, Aneta D. Sabovljević^1,2, Marko S. Sabovljević^1,2,4,*

Phyton-International Journal of Experimental Botany, Vol.93, No.11, pp. 3039-3054, 2024, DOI:10.32604/phyton.2024.058469 - 30 November 2024

Abstract The rare and threatened semi-aquatic moss Drepanocladus lycopodioides (Amblystegiaceae) was the subject of growth optimization under ex situ axenic laboratory conditions. The positioning of the plantlets on media, media types as well as selected growth regulators and sugars were parameters tested in optimizing growth promotion of this species in captivity. Out of the tested media types, the KNOP medium and the upright positioning of the explants were the best for propagation and biomass production of D. lycopodioides. The addition of sugars had no significant effect on this moss development axenically, while exogenously applied Benzylaminopurine (BAP) at a… More >