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  • Open Access

    ARTICLE

    A Smart Obfuscation Approach to Protect Software in Cloud

    Lei Yu1, Yucong Duan2,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3949-3965, 2023, DOI:10.32604/cmc.2023.038970 - 08 October 2023

    Abstract Cloud computing and edge computing brought more software, which also brought a new danger of malicious software attacks. Data synchronization mechanisms of software can further help reverse data modifications. Based on the mechanisms, attackers can cover themselves behind the network and modify data undetected. Related knowledge of software reverse engineering can be organized as rules to accelerate the attacks, when attackers intrude cloud server to access the source or binary codes. Therefore, we proposed a novel method to resist this kind of reverse engineering by breaking these rules. Our method is based on software obfuscations… More >

  • Open Access

    ARTICLE

    A Transmission and Transformation Fault Detection Algorithm Based on Improved YOLOv5

    Xinliang Tang1, Xiaotong Ru1, Jingfang Su1,*, Gabriel Adonis2

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2997-3011, 2023, DOI:10.32604/cmc.2023.038923 - 08 October 2023

    Abstract On the transmission line, the invasion of foreign objects such as kites, plastic bags, and balloons and the damage to electronic components are common transmission line faults. Detecting these faults is of great significance for the safe operation of power systems. Therefore, a YOLOv5 target detection method based on a deep convolution neural network is proposed. In this paper, Mobilenetv2 is used to replace Cross Stage Partial (CSP)-Darknet53 as the backbone. The structure uses depth-wise separable convolution toreduce the amount of calculation and parameters; improve the detection rate. At the same time, to compensate for… More >

  • Open Access

    ARTICLE

    Deep-Net: Fine-Tuned Deep Neural Network Multi-Features Fusion for Brain Tumor Recognition

    Muhammad Attique Khan1,2, Reham R. Mostafa3, Yu-Dong Zhang2, Jamel Baili4, Majed Alhaisoni5, Usman Tariq6, Junaid Ali Khan1, Ye Jin Kim7, Jaehyuk Cha7,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3029-3047, 2023, DOI:10.32604/cmc.2023.038838 - 08 October 2023

    Abstract Manual diagnosis of brain tumors using magnetic resonance images (MRI) is a hectic process and time-consuming. Also, it always requires an expert person for the diagnosis. Therefore, many computer-controlled methods for diagnosing and classifying brain tumors have been introduced in the literature. This paper proposes a novel multimodal brain tumor classification framework based on two-way deep learning feature extraction and a hybrid feature optimization algorithm. NasNet-Mobile, a pre-trained deep learning model, has been fine-tuned and two-way trained on original and enhanced MRI images. The haze-convolutional neural network (haze-CNN) approach is developed and employed on the… More >

  • Open Access

    ARTICLE

    Ensemble of Population-Based Metaheuristic Algorithms

    Hao Li, Jun Tang*, Qingtao Pan, Jianjun Zhan, Songyang Lao

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2835-2859, 2023, DOI:10.32604/cmc.2023.038670 - 08 October 2023

    Abstract No optimization algorithm can obtain satisfactory results in all optimization tasks. Thus, it is an effective way to deal with the problem by an ensemble of multiple algorithms. This paper proposes an ensemble of population-based metaheuristics (EPM) to solve single-objective optimization problems. The design of the EPM framework includes three stages: the initial stage, the update stage, and the final stage. The framework applies the transformation of the real and virtual population to balance the problem of exploration and exploitation at the population level and uses an elite strategy to communicate among virtual populations. The… More >

  • Open Access

    ARTICLE

    Traffic Scene Captioning with Multi-Stage Feature Enhancement

    Dehai Zhang*, Yu Ma, Qing Liu, Haoxing Wang, Anquan Ren, Jiashu Liang

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2901-2920, 2023, DOI:10.32604/cmc.2023.038264 - 08 October 2023

    Abstract Traffic scene captioning technology automatically generates one or more sentences to describe the content of traffic scenes by analyzing the content of the input traffic scene images, ensuring road safety while providing an important decision-making function for sustainable transportation. In order to provide a comprehensive and reasonable description of complex traffic scenes, a traffic scene semantic captioning model with multi-stage feature enhancement is proposed in this paper. In general, the model follows an encoder-decoder structure. First, multi-level granularity visual features are used for feature enhancement during the encoding process, which enables the model to learn… More >

  • Open Access

    ARTICLE

    AI-Driven FBMC-OQAM Signal Recognition via Transform Channel Convolution Strategy

    Zeliang An1, Tianqi Zhang1,*, Debang Liu1, Yuqing Xu2, Gert Frølund Pedersen2, Ming Shen2

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2817-2834, 2023, DOI:10.32604/cmc.2023.037832 - 08 October 2023

    Abstract With the advent of the Industry 5.0 era, the Internet of Things (IoT) devices face unprecedented proliferation, requiring higher communications rates and lower transmission delays. Considering its high spectrum efficiency, the promising filter bank multicarrier (FBMC) technique using offset quadrature amplitude modulation (OQAM) has been applied to Beyond 5G (B5G) industry IoT networks. However, due to the broadcasting nature of wireless channels, the FBMC-OQAM industry IoT network is inevitably vulnerable to adversary attacks from malicious IoT nodes. The FBMC-OQAM industry cognitive radio network (ICRNet) is proposed to ensure security at the physical layer to tackle… More >

  • Open Access

    ARTICLE

    Reliability Analysis of Correlated Competitive and Dependent Components Considering Random Isolation Times

    Shuo Cai1, Tingyu Luo1, Fei Yu1,*, Pradip Kumar Sharma2, Weizheng Wang1, Lairong Yin3

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2763-2777, 2023, DOI:10.32604/cmc.2023.037825 - 08 October 2023

    Abstract In the Internet of Things (IoT) system, relay communication is widely used to solve the problem of energy loss in long-distance transmission and improve transmission efficiency. In Body Sensor Network (BSN) systems, biosensors communicate with receiving devices through relay nodes to improve their limited energy efficiency. When the relay node fails, the biosensor can communicate directly with the receiving device by releasing more transmitting power. However, if the remaining battery power of the biosensor is insufficient to enable it to communicate directly with the receiving device, the biosensor will be isolated by the system. Therefore, More >

  • Open Access

    ARTICLE

    A New Partial Task Offloading Method in a Cooperation Mode under Multi-Constraints for Multi-UE

    Shengyao Sun1,2, Ying Du3, Jiajun Chen4, Xuan Zhang5, Jiwei Zhang6,*, Yiyi Xu7

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2879-2900, 2023, DOI:10.32604/cmc.2023.037483 - 08 October 2023

    Abstract In Multi-access Edge Computing (MEC), to deal with multiple user equipment (UE)’s task offloading problem of parallel relationships under the multi-constraints, this paper proposes a cooperation partial task offloading method (named CPMM), aiming to reduce UE's energy and computation consumption, while meeting the task completion delay as much as possible. CPMM first studies the task offloading of single-UE and then considers the task offloading of multi-UE based on single-UE task offloading. CPMM uses the critical path algorithm to divide the modules into key and non-key modules. According to some constraints of UE-self when offloading tasks,… More >

  • Open Access

    ARTICLE

    A Multilevel Hierarchical Parallel Algorithm for Large-Scale Finite Element Modal Analysis

    Gaoyuan Yu1, Yunfeng Lou2, Hang Dong3, Junjie Li1, Xianlong Jin1,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2795-2816, 2023, DOI:10.32604/cmc.2023.037375 - 08 October 2023

    Abstract The strict and high-standard requirements for the safety and stability of major engineering systems make it a tough challenge for large-scale finite element modal analysis. At the same time, realizing the systematic analysis of the entire large structure of these engineering systems is extremely meaningful in practice. This article proposes a multilevel hierarchical parallel algorithm for large-scale finite element modal analysis to reduce the parallel computational efficiency loss when using heterogeneous multicore distributed storage computers in solving large-scale finite element modal analysis. Based on two-level partitioning and four-transformation strategies, the proposed algorithm not only improves… More >

  • Open Access

    ARTICLE

    Honeypot Game Theory against DoS Attack in UAV Cyber

    Shangting Miao1, Yang Li2,*, Quan Pan2

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2745-2762, 2023, DOI:10.32604/cmc.2023.037257 - 08 October 2023

    Abstract A space called Unmanned Aerial Vehicle (UAV) cyber is a new environment where UAV, Ground Control Station (GCS) and business processes are integrated. Denial of service (DoS) attack is a standard network attack method, especially suitable for attacking the UAV cyber. It is a robust security risk for UAV cyber and has recently become an active research area. Game theory is typically used to simulate the existing offensive and defensive mechanisms for DoS attacks in a traditional network. In addition, the honeypot, an effective security vulnerability defense mechanism, has not been widely adopted or modeled… More >

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