Wei Wu, Liang Yu, Liping Yang^*, Yadong Zhang, Peng Wang

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 587-603, 2024, DOI:10.32604/cmc.2024.052655

Abstract As an open network architecture, Wireless Computing Power Networks (WCPN) pose new challenges for achieving efficient and secure resource management in networks, because of issues such as insecure communication channels and untrusted device terminals. Blockchain, as a shared, immutable distributed ledger, provides a secure resource management solution for WCPN. However, integrating blockchain into WCPN faces challenges like device heterogeneity, monitoring communication states, and dynamic network nature. Whereas Digital Twins (DT) can accurately maintain digital models of physical entities through real-time data updates and self-learning, enabling continuous optimization of WCPN, improving synchronization performance, ensuring real-time accuracy, More >

Waseem Akram¹, Khalid Mahmood², Hafiz Burhan ul Haq³, Muhammad Asif³, Shehzad Ashraf Chaudhry^4,5, Taeshik Shon^6,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 263-280, 2024, DOI:10.32604/cmc.2024.052405

Abstract Cookies are considered a fundamental means of web application services for authenticating various Hypertext Transfer Protocol (HTTP) requests and maintains the states of clients’ information over the Internet. HTTP cookies are exploited to carry client patterns observed by a website. These client patterns facilitate the particular client’s future visit to the corresponding website. However, security and privacy are the primary concerns owing to the value of information over public channels and the storage of client information on the browser. Several protocols have been introduced that maintain HTTP cookies, but many of those fail to achieve More >

Feng Zhao¹, Hongtao Ding², Chunhai Li^1,*, Zhaoyu Su², Guoling Liang², Changsong Yang³

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 567-585, 2024, DOI:10.32604/cmc.2024.052233

Abstract The Internet of Vehicles (IoV) is extensively deployed in outdoor and open environments to effectively address traffic efficiency and safety issues by connecting vehicles to the network. However, due to the open and variable nature of its network topology, vehicles frequently engage in cross-domain interactions. During such processes, directly uploading sensitive information to roadside units for interaction may expose it to malicious tampering or interception by attackers, thus compromising the security of the cross-domain authentication process. Additionally, IoV imposes high real-time requirements, and existing cross-domain authentication schemes for IoV often encounter efficiency issues. To mitigate More >

Li Li^*, Qing Zhang, Youran Kong

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 801-818, 2024, DOI:10.32604/cmc.2024.051916

Abstract Due to the diversity and unpredictability of changes in malicious code, studying the traceability of variant families remains challenging. In this paper, we propose a GAN-EfficientNetV2-based method for tracing families of malicious code variants. This method leverages the similarity in layouts and textures between images of malicious code variants from the same source and their original family of malicious code images. The method includes a lightweight classifier and a simulator. The classifier utilizes the enhanced EfficientNetV2 to categorize malicious code images and can be easily deployed on mobile, embedded, and other devices. The simulator utilizes… More >

Jieren Cheng^1,3, Jimei Li^1,3,*, Faqiang Zeng^1,3, Zhicong Tao^1,3, Yue Yang^2,3

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 281-298, 2024, DOI:10.32604/cmc.2024.051816

Abstract Contrastive learning is a significant research direction in the field of deep learning. However, existing data augmentation methods often lead to issues such as semantic drift in generated views while the complexity of model pre-training limits further improvement in the performance of existing methods. To address these challenges, we propose the Efficient Clustering Network based on Matrix Factorization (ECN-MF). Specifically, we design a batched low-rank Singular Value Decomposition (SVD) algorithm for data augmentation to eliminate redundant information and uncover major patterns of variation and key information in the data. Additionally, we design a Mutual Information-Enhanced More >

Anas AbuKaraki¹, Tawfi Alrawashdeh¹, Sumaya Abusaleh¹, Malek Zakarya Alksasbeh^1,*, Bilal Alqudah¹, Khalid Alemerien², Hamzah Alshamaseen³

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1055-1073, 2024, DOI:10.32604/cmc.2024.051420

Abstract This paper presents a novel multiclass system designed to detect pleural effusion and pulmonary edema on chest X-ray images, addressing the critical need for early detection in healthcare. A new comprehensive dataset was formed by combining 28,309 samples from the ChestX-ray14, PadChest, and CheXpert databases, with 10,287, 6022, and 12,000 samples representing Pleural Effusion, Pulmonary Edema, and Normal cases, respectively. Consequently, the preprocessing step involves applying the Contrast Limited Adaptive Histogram Equalization (CLAHE) method to boost the local contrast of the X-ray samples, then resizing the images to 380 × 380 dimensions, followed by using the data… More >

Ambika Aggarwal¹, Sunil Kumar^2,3, Ashok Bhansali⁴, Deema Mohammed Alsekait^5,*, Diaa Salama AbdElminaam^6,7,8

Computer Systems Science and Engineering, Vol.48, No.4, pp. 953-967, 2024, DOI:10.32604/csse.2024.050406

Abstract Existing multiple workflow scheduling techniques focus on traditional Quality of Service (QoS) parameters such as cost, deadline, and makespan to find optimal solutions by consuming a large amount of electrical energy. Higher energy consumption decreases system efficiency, increases operational cost, and generates more carbon footprint. These major problems can lead to several problems, such as economic strain, environmental degradation, resource depletion, energy dependence, health impacts, etc. In a cloud computing environment, scheduling multiple workflows is critical in developing a strategy for energy optimization, which is an NP-hard problem. This paper proposes a novel, bi-phase Energy-Efficient… More >

Punam Gulande^*, R. N. Awale

Computer Systems Science and Engineering, Vol.48, No.4, pp. 937-952, 2024, DOI:10.32604/csse.2024.046123

Abstract The study of gene expression has emerged as a vital tool for cancer diagnosis and prognosis, particularly with the advent of microarray technology that enables the measurement of thousands of genes in a single sample. While this wealth of data offers invaluable insights for disease management, the high dimensionality poses a challenge for multiclass classification. In this context, selecting relevant features becomes essential to enhance classification model performance. Swarm Intelligence algorithms have proven effective in addressing this challenge, owing to their ability to navigate intricate, non-linear feature-class relationships. This paper introduces a novel hybrid swarm More >

Meignanamoorthi Dhandapani^*, V. Vetriselvi, R. Aishwarya

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2449-2486, 2024, DOI:10.32604/cmes.2024.050986

Abstract The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global scale. Network slicing is crucial in delivering services for different, demanding vertical applications in this context. Next-generation applications have time-sensitive requirements and depend on the most efficient routing path to ensure packets reach their intended destinations. However, the existing IP (Internet Protocol) over a multi-domain network faces challenges in enforcing network slicing due to minimal collaboration and information sharing among network operators. Conventional inter-domain routing methods, like Border Gateway Protocol (BGP), cannot make routing decisions based on performance,… More >

Chen Xing¹, Leihua Yao^1,*, Yingdong Wang²

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2825-2848, 2024, DOI:10.32604/cmes.2024.049330

Abstract In pumped storage projects, the permeability of rock masses is a crucial parameter in engineering design and construction. The rock mass permeability coefficient (K) is influenced by various geological parameters, and previous studies aimed to establish an accurate relationship between K and geological parameters. This study uses the improved sparrow search algorithm (ISSA) to optimize the parameter settings of the deep extreme learning machine (DELM), constructing a prediction model with flexible parameter selection and high accuracy. First, the Spearman method is applied to analyze the correlation between geological parameters. A sample database is built by comprehensively… More >