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  • Open Access

    ARTICLE

    Clustering-Aided Supervised Malware Detection with Specialized Classifiers and Early Consensus

    Murat Dener*, Sercan Gulburun

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1235-1251, 2023, DOI:10.32604/cmc.2023.036357 - 06 February 2023

    Abstract One of the most common types of threats to the digital world is malicious software. It is of great importance to detect and prevent existing and new malware before it damages information assets. Machine learning approaches are used effectively for this purpose. In this study, we present a model in which supervised and unsupervised learning algorithms are used together. Clustering is used to enhance the prediction performance of the supervised classifiers. The aim of the proposed model is to make predictions in the shortest possible time with high accuracy and f1 score. In the first… More >

  • Open Access

    ARTICLE

    A Novel Meta-Heuristic Optimization Algorithm in White Blood Cells Classification

    Khaled A. Fathy, Humam K. Yaseen*, Mohammad T. Abou-Kreisha, Kamal A. ElDahshan

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1527-1545, 2023, DOI:10.32604/cmc.2023.036322 - 06 February 2023

    Abstract Some human diseases are recognized through of each type of White Blood Cell (WBC) count, so detecting and classifying each type is important for human healthcare. The main aim of this paper is to propose a computer-aided WBCs utility analysis tool designed, developed, and evaluated to classify WBCs into five types namely neutrophils, eosinophils, lymphocytes, monocytes, and basophils. Using a computer-artificial model reduces resource and time consumption. Various pre-trained deep learning models have been used to extract features, including AlexNet, Visual Geometry Group (VGG), Residual Network (ResNet), which belong to different taxonomy types of deep… More >

  • Open Access

    ARTICLE

    Robust Multi-Watermarking Algorithm for Medical Images Based on GoogLeNet and Henon Map

    Wenxing Zhang1, Jingbing Li1,2,*, Uzair Aslam Bhatti1,2, Jing Liu3, Junhua Zheng1, Yen-Wei Chen4

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 565-586, 2023, DOI:10.32604/cmc.2023.036317 - 06 February 2023

    Abstract The field of medical images has been rapidly evolving since the advent of the digital medical information era. However, medical data is susceptible to leaks and hacks during transmission. This paper proposed a robust multi-watermarking algorithm for medical images based on GoogLeNet transfer learning to protect the privacy of patient data during transmission and storage, as well as to increase the resistance to geometric attacks and the capacity of embedded watermarks of watermarking algorithms. First, a pre-trained GoogLeNet network is used in this paper, based on which the parameters of several previous layers of the… More >

  • Open Access

    ARTICLE

    An Active Image Forgery Detection Approach Based on Edge Detection

    Hüseyin Bilal Macit1, Arif Koyun2,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1603-1619, 2023, DOI:10.32604/cmc.2023.036216 - 06 February 2023

    Abstract Recently, digital images have become the most used data, thanks to high internet speed and high resolution, cheap and easily accessible digital cameras. We generate, transmit and store millions of images every second. Most of these images are insignificant images containing only personal information. However, in many fields such as banking, finance, public institutions, and educational institutions, the images of many valuable objects like ID cards, photographs, credit cards, and transaction receipts are stored and transmitted to the digital environment. These images are very significant and must be secured. A valuable image can be maliciously… More >

  • Open Access

    ARTICLE

    Fast Detection and Classification of Dangerous Urban Sounds Using Deep Learning

    Zeinel Momynkulov1, Zhandos Dosbayev2,3,*, Azizah Suliman4, Bayan Abduraimova5, Nurzhigit Smailov2, Maigul Zhekambayeva2, Dusmat Zhamangarin6

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2191-2208, 2023, DOI:10.32604/cmc.2023.036205 - 06 February 2023

    Abstract Video analytics is an integral part of surveillance cameras. Compared to video analytics, audio analytics offers several benefits, including less expensive equipment and upkeep expenses. Additionally, the volume of the audio datastream is substantially lower than the video camera datastream, especially concerning real-time operating systems, which makes it less demanding of the data channel’s bandwidth needs. For instance, automatic live video streaming from the site of an explosion and gunshot to the police console using audio analytics technologies would be exceedingly helpful for urban surveillance. Technologies for audio analytics may also be used to analyze More >

  • Open Access

    ARTICLE

    Lattice-Based Authentication Scheme to Prevent Quantum Attack in Public Cloud Environment

    Naveed Khan1, Zhang Jianbiao1, Intikhab Ullah2, Muhammad Salman Pathan3, Huhnkuk Lim4,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 35-49, 2023, DOI:10.32604/cmc.2023.036189 - 06 February 2023

    Abstract Public cloud computing provides a variety of services to consumers via high-speed internet. The consumer can access these services anytime and anywhere on a balanced service cost. Many traditional authentication protocols are proposed to secure public cloud computing. However, the rapid development of high-speed internet and organizations’ race to develop quantum computers is a nightmare for existing authentication schemes. These traditional authentication protocols are based on factorization or discrete logarithm problems. As a result, traditional authentication protocols are vulnerable in the quantum computing era. Therefore, in this article, we have proposed an authentication protocol based More >

  • Open Access

    ARTICLE

    SiamDLA: Dynamic Label Assignment for Siamese Visual Tracking

    Yannan Cai, Ke Tan, Zhenzhong Wei*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1621-1640, 2023, DOI:10.32604/cmc.2023.036177 - 06 February 2023

    Abstract Label assignment refers to determining positive/negative labels for each sample to supervise the training process. Existing Siamese-based trackers primarily use fixed label assignment strategies according to human prior knowledge; thus, they can be sensitive to predefined hyperparameters and fail to fit the spatial and scale variations of samples. In this study, we first develop a novel dynamic label assignment (DLA) module to handle the diverse data distributions and adaptively distinguish the foreground from the background based on the statistical characteristics of the target in visual object tracking. The core of DLA module is a two-step… More >

  • Open Access

    ARTICLE

    Estimation of Weibull Distribution Parameters for Wind Speed Characteristics Using Neural Network Algorithm

    Musaed Alrashidi*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1073-1088, 2023, DOI:10.32604/cmc.2023.036170 - 06 February 2023

    Abstract Harvesting the power coming from the wind provides a green and environmentally friendly approach to producing electricity. To facilitate the ongoing advancement in wind energy applications, deep knowledge about wind regime behavior is essential. Wind speed is typically characterized by a statistical distribution, and the two-parameters Weibull distribution has shown its ability to represent wind speeds worldwide. Estimation of Weibull parameters, namely scale and shape parameters, is vital to describe the observed wind speeds data accurately. Yet, it is still a challenging task. Several numerical estimation approaches have been used by researchers to obtain c and… More >

  • Open Access

    ARTICLE

    Received Power Based Unmanned Aerial Vehicles (UAVs) Jamming Detection and Nodes Classification Using Machine Learning

    Waleed Aldosari*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1253-1269, 2023, DOI:10.32604/cmc.2023.036111 - 06 February 2023

    Abstract This paper presents a machine-learning method for detecting jamming UAVs and classifying nodes during jamming attacks on Wireless Sensor Networks (WSNs). Jamming is a type of Denial of Service (DoS) attack and intentional interference where a malicious node transmits a high-power signal to increase noise on the receiver side to disrupt the communication channel and reduce performance significantly. To defend and prevent such attacks, the first step is to detect them. The current detection approaches use centralized techniques to detect jamming, where each node collects information and forwards it to the base station. As a… More >

  • Open Access

    ARTICLE

    Dynamic Behavior-Based Churn Forecasts in the Insurance Sector

    Nagaraju Jajam, Nagendra Panini Challa*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 977-997, 2023, DOI:10.32604/cmc.2023.036098 - 06 February 2023

    Abstract In the insurance sector, a massive volume of data is being generated on a daily basis due to a vast client base. Decision makers and business analysts emphasized that attaining new customers is costlier than retaining existing ones. The success of retention initiatives is determined not only by the accuracy of forecasting churners but also by the timing of the forecast. Previous works on churn forecast presented models for anticipating churn quarterly or monthly with an emphasis on customers’ static behavior. This paper’s objective is to calculate daily churn based on dynamic variations in client… More >

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