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  • Open Access

    REVIEW

    Plant Extracts as Biostimulant Agents: A Promising Strategy for Managing Environmental Stress in Sustainable Agriculture

    Mingzhao Han1, Susilawati Kasim1,*, Zhongming Yang2, Xi Deng2, Noor Baity Saidi3, Md Kamal Uddin1, Effyanti Mohd Shuib1

    Phyton-International Journal of Experimental Botany, Vol.93, No.9, pp. 2149-2166, 2024, DOI:10.32604/phyton.2024.054009 - 30 September 2024

    Abstract It is imperative to enhance crop yield to meet the demands of a burgeoning global population while simultaneously safeguarding the environment from adverse impacts, which is one of the dominant challenges confronting humanity in this phase of global climate change. To overcome this problem and reduce dependency on chemical fertilizer, scientists now view the implementation of biostimulant strategies as a cost-effective and environmentally friendly approach to achieving sustainable agriculture. Plant extracts are rich in bioactive phytocompounds, which can enhance plant resistance to disease, pest, and abiotic stresses (e.g., drought, salinity, and extreme temperature), and promote… More >

  • Open Access

    ARTICLE

    AI-Powered Image Security: Utilizing Autoencoders for Advanced Medical Image Encryption

    Fehaid Alqahtani*

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1709-1724, 2024, DOI:10.32604/cmes.2024.054976 - 27 September 2024

    Abstract With the rapid advancement in artificial intelligence (AI) and its application in the Internet of Things (IoT), intelligent technologies are being introduced in the medical field, giving rise to smart healthcare systems. The medical imaging data contains sensitive information, which can easily be stolen or tampered with, necessitating secure encryption schemes designed specifically to protect these images. This paper introduces an artificial intelligence-driven novel encryption scheme tailored for the secure transmission and storage of high-resolution medical images. The proposed scheme utilizes an artificial intelligence-based autoencoder to compress high-resolution medical images and to facilitate fast encryption… More >

  • Open Access

    ARTICLE

    Task Offloading and Trajectory Optimization in UAV Networks: A Deep Reinforcement Learning Method Based on SAC and A-Star

    Jianhua Liu*, Peng Xie, Jiajia Liu, Xiaoguang Tu

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1243-1273, 2024, DOI:10.32604/cmes.2024.054002 - 27 September 2024

    Abstract In mobile edge computing, unmanned aerial vehicles (UAVs) equipped with computing servers have emerged as a promising solution due to their exceptional attributes of high mobility, flexibility, rapid deployment, and terrain agnosticism. These attributes enable UAVs to reach designated areas, thereby addressing temporary computing swiftly in scenarios where ground-based servers are overloaded or unavailable. However, the inherent broadcast nature of line-of-sight transmission methods employed by UAVs renders them vulnerable to eavesdropping attacks. Meanwhile, there are often obstacles that affect flight safety in real UAV operation areas, and collisions between UAVs may also occur. To solve… More >

  • Open Access

    ARTICLE

    IWTW: A Framework for IoWT Cyber Threat Analysis

    GyuHyun Jeon1, Hojun Jin1, Ju Hyeon Lee1, Seungho Jeon2, Jung Taek Seo2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1575-1622, 2024, DOI:10.32604/cmes.2024.053465 - 27 September 2024

    Abstract The Internet of Wearable Things (IoWT) or Wearable Internet of Things (WIoT) is a new paradigm that combines IoT and wearable technology. Advances in IoT technology have enabled the miniaturization of sensors embedded in wearable devices and the ability to communicate data and access real-time information over low-power mobile networks. IoWT devices are highly interdependent with mobile devices. However, due to their limited processing power and bandwidth, IoWT devices are vulnerable to cyberattacks due to their low level of security. Threat modeling and frameworks for analyzing cyber threats against existing IoT or low-power protocols have… More >

  • Open Access

    ARTICLE

    Encrypted Cyberattack Detection System over Encrypted IoT Traffic Based on Statistical Intelligence

    Il Hwan Ji1, Ju Hyeon Lee1, Seungho Jeon2, Jung Taek Seo2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1519-1549, 2024, DOI:10.32604/cmes.2024.053437 - 27 September 2024

    Abstract In the early days of IoT’s introduction, it was challenging to introduce encryption communication due to the lack of performance of each component, such as computing resources like CPUs and batteries, to encrypt and decrypt data. Because IoT is applied and utilized in many important fields, a cyberattack on IoT can result in astronomical financial and human casualties. For this reason, the application of encrypted communication to IoT has been required, and the application of encrypted communication to IoT has become possible due to improvements in the computing performance of IoT devices and the development… More >

  • Open Access

    ARTICLE

    Advancing 5G Network Applications Lifecycle Security: An ML-Driven Approach

    Ana Hermosilla1,2,*, Jorge Gallego-Madrid1, Pedro Martinez-Julia3, Jordi Ortiz4, Ved P. Kafle3, Antonio Skarmeta1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1447-1471, 2024, DOI:10.32604/cmes.2024.053379 - 27 September 2024

    Abstract As 5th Generation (5G) and Beyond 5G (B5G) networks become increasingly prevalent, ensuring not only network security but also the security and reliability of the applications, the so-called network applications, becomes of paramount importance. This paper introduces a novel integrated model architecture, combining a network application validation framework with an AI-driven reactive system to enhance security in real-time. The proposed model leverages machine learning (ML) and artificial intelligence (AI) to dynamically monitor and respond to security threats, effectively mitigating potential risks before they impact the network infrastructure. This dual approach not only validates the functionality… More >

  • Open Access

    ARTICLE

    Post-COVID-19 Challenges for Full-Time Employees in China: Job Insecurity, Workplace Anxiety and Work-Life Conflict

    Tianfei Yang1, Xianyi Long2,*

    International Journal of Mental Health Promotion, Vol.26, No.9, pp. 719-730, 2024, DOI:10.32604/ijmhp.2024.053705 - 20 September 2024

    Abstract Background: Though the COVID-19 pandemic recedes, and our society gradually returns to normal, Chinese people’s work and lifestyles are still influenced by the “pandemic aftermath”. In the post-pandemic era, employees may feel uncertainty at work due to the changed organizational operations and management and perceive the external environment to be more dynamic. Both these perceptions may increase employees’ negative emotions and contribute to conflicts between work and life. Drawing from the ego depletion theory, this study aimed to examine the impact of job insecurity during the post-pandemic era on employees’ work-life conflicts, and the mediating… More >

  • Open Access

    ARTICLE

    Research on computer network data security storage technology in the era of big data

    Liying Zhang1, Xin Gu1, Qiang Zhao2

    Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, Vol.40, No.2, pp. 1-7, 2024, DOI:10.23967/j.rimni.2024.05.001 - 17 May 2024

    Abstract In the burgeoning epoch of big data, the imperative for secure computer network data storage is confronted with formidable challenges, including the perils of data breaches and a paucity of robust security measures. An enhanced storage paradigm, predicated upon a refined Hash algorithm—termed H-AONT—is herein delineated. This methodology augments data storage security through the formulation of an apposite system model, the amalgamation of the merits inherent in conventional encryption algorithms, and the deployment of the H-AONT dual encryption algorithm in data processing. Empirical evidence substantiates that, vis-à-vis alternative approaches, the proposed method significantly bolsters data More >

  • Open Access

    ARTICLE

    Adaptable and Dynamic Access Control Decision-Enforcement Approach Based on Multilayer Hybrid Deep Learning Techniques in BYOD Environment

    Aljuaid Turkea Ayedh M1,2,*, Ainuddin Wahid Abdul Wahab1,*, Mohd Yamani Idna Idris1,3

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4663-4686, 2024, DOI:10.32604/cmc.2024.055287 - 12 September 2024

    Abstract Organizations are adopting the Bring Your Own Device (BYOD) concept to enhance productivity and reduce expenses. However, this trend introduces security challenges, such as unauthorized access. Traditional access control systems, such as Attribute-Based Access Control (ABAC) and Role-Based Access Control (RBAC), are limited in their ability to enforce access decisions due to the variability and dynamism of attributes related to users and resources. This paper proposes a method for enforcing access decisions that is adaptable and dynamic, based on multilayer hybrid deep learning techniques, particularly the Tabular Deep Neural Network TabularDNN method. This technique transforms… More >

  • Open Access

    ARTICLE

    An Improved Image Steganography Security and Capacity Using Ant Colony Algorithm Optimization

    Zinah Khalid Jasim Jasim*, Sefer Kurnaz*

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4643-4662, 2024, DOI:10.32604/cmc.2024.055195 - 12 September 2024

    Abstract This advanced paper presents a new approach to improving image steganography using the Ant Colony Optimization (ACO) algorithm. Image steganography, a technique of embedding hidden information in digital photographs, should ideally achieve the dual purposes of maximum data hiding and maintenance of the integrity of the cover media so that it is least suspect. The contemporary methods of steganography are at best a compromise between these two. In this paper, we present our approach, entitled Ant Colony Optimization (ACO)-Least Significant Bit (LSB), which attempts to optimize the capacity in steganographic embedding. The approach makes use… More >

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