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  • Open Access

    ARTICLE

    High Performance Classification of Android Malware Using Ensemble Machine Learning

    Pagnchakneat C. Ouk1, Wooguil Pak2,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 381-398, 2022, DOI:10.32604/cmc.2022.024540

    Abstract Although Android becomes a leading operating system in market, Android users suffer from security threats due to malwares. To protect users from the threats, the solutions to detect and identify the malware variant are essential. However, modern malware evades existing solutions by applying code obfuscation and native code. To resolve this problem, we introduce an ensemble-based malware classification algorithm using malware family grouping. The proposed family grouping algorithm finds the optimal combination of families belonging to the same group while the total number of families is fixed to the optimal total number. It also adopts… More >

  • Open Access

    ARTICLE

    An Evolutionary Normalization Algorithm for Signed Floating-Point Multiply-Accumulate Operation

    Rajkumar Sarma1, Cherry Bhargava2, Ketan Kotecha3,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 481-495, 2022, DOI:10.32604/cmc.2022.024516

    Abstract In the era of digital signal processing, like graphics and computation systems, multiplication-accumulation is one of the prime operations. A MAC unit is a vital component of a digital system, like different Fast Fourier Transform (FFT) algorithms, convolution, image processing algorithms, etcetera. In the domain of digital signal processing, the use of normalization architecture is very vast. The main objective of using normalization is to perform comparison and shift operations. In this research paper, an evolutionary approach for designing an optimized normalization algorithm is proposed using basic logical blocks such as Multiplexer, Adder etc. The… More >

  • Open Access

    ARTICLE

    Efficient Approach for Resource Allocation in WPCN Using Hybrid Optimization

    Richu Mary Thomas, Malarvizhi Subramani*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1275-1291, 2022, DOI:10.32604/cmc.2022.024507

    Abstract The recent aggrandizement of radio frequency (RF) signals in wireless power transmission combined with energy harvesting methods have led to the replacement of traditional battery-powered wireless networks since the blooming RF technology provides energy renewal of wireless devices with the quality of service (QoS). In addition, it does not require any unnecessary alterations on the transmission hardware side. A hybridized global optimization technique uniting Global best and Local best (GL) based particle swarm optimization (PSO) and ant colony optimization (ACO) is proposed in this paper to optimally allocate resources in wireless powered communication networks (WPCN)… More >

  • Open Access

    ARTICLE

    Malware Detection Using Decision Tree Based SVM Classifier for IoT

    Anwer Mustafa Hilal1,*, Siwar Ben Haj Hassine2, Souad Larabi-Marie-Sainte3, Nadhem Nemri2, Mohamed K. Nour4, Abdelwahed Motwakel1, Abu Sarwar Zamani1, Mesfer Al Duhayyim5

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 713-726, 2022, DOI:10.32604/cmc.2022.024501

    Abstract The development in Information and Communication Technology has led to the evolution of new computing and communication environment. Technological revolution with Internet of Things (IoTs) has developed various applications in almost all domains from health care, education to entertainment with sensors and smart devices. One of the subsets of IoT is Internet of Medical things (IoMT) which connects medical devices, hardware and software applications through internet. IoMT enables secure wireless communication over the Internet to allow efficient analysis of medical data. With these smart advancements and exploitation of smart IoT devices in health care technology… More >

  • Open Access

    ARTICLE

    Anomaly Detection for Internet of Things Cyberattacks

    Manal Alanazi*, Ahamed Aljuhani

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 261-279, 2022, DOI:10.32604/cmc.2022.024496

    Abstract The Internet of Things (IoT) has been deployed in diverse critical sectors with the aim of improving quality of service and facilitating human lives. The IoT revolution has redefined digital services in different domains by improving efficiency, productivity, and cost-effectiveness. Many service providers have adapted IoT systems or plan to integrate them as integral parts of their systems’ operation; however, IoT security issues remain a significant challenge. To minimize the risk of cyberattacks on IoT networks, anomaly detection based on machine learning can be an effective security solution to overcome a wide range of IoT… More >

  • Open Access

    ARTICLE

    Deep Learning and Machine Learning for Early Detection of Stroke and Haemorrhage

    Zeyad Ghaleb Al-Mekhlafi1, Ebrahim Mohammed Senan2, Taha H. Rassem3, Badiea Abdulkarem Mohammed4,5,*, Nasrin M. Makbol5, Adwan Alownie Alanazi1, Tariq S. Almurayziq1, Fuad A. Ghaleb6

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 775-796, 2022, DOI:10.32604/cmc.2022.024492

    Abstract Stroke and cerebral haemorrhage are the second leading causes of death in the world after ischaemic heart disease. In this work, a dataset containing medical, physiological and environmental tests for stroke was used to evaluate the efficacy of machine learning, deep learning and a hybrid technique between deep learning and machine learning on the Magnetic Resonance Imaging (MRI) dataset for cerebral haemorrhage. In the first dataset (medical records), two features, namely, diabetes and obesity, were created on the basis of the values of the corresponding features. The t-Distributed Stochastic Neighbour Embedding algorithm was applied to… More >

  • Open Access

    ARTICLE

    Optimal Deep Learning-based Cyberattack Detection and Classification Technique on Social Networks

    Amani Abdulrahman Albraikan1, Siwar Ben Haj Hassine2, Suliman Mohamed Fati3, Fahd N. Al-Wesabi2,4, Anwer Mustafa Hilal5,*, Abdelwahed Motwakel5, Manar Ahmed Hamza5, Mesfer Al Duhayyim6

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 907-923, 2022, DOI:10.32604/cmc.2022.024488

    Abstract Cyberbullying (CB) is a distressing online behavior that disturbs mental health significantly. Earlier studies have employed statistical and Machine Learning (ML) techniques for CB detection. With this motivation, the current paper presents an Optimal Deep Learning-based Cyberbullying Detection and Classification (ODL-CDC) technique for CB detection in social networks. The proposed ODL-CDC technique involves different processes such as pre-processing, prediction, and hyperparameter optimization. In addition, GloVe approach is employed in the generation of word embedding. Besides, the pre-processed data is fed into Bidirectional Gated Recurrent Neural Network (BiGRNN) model for prediction. Moreover, hyperparameter tuning of BiGRNN More >

  • Open Access

    ARTICLE

    Stochastic Epidemic Model of Covid-19 via the Reservoir-People Transmission Network

    Kazem Nouri1,*, Milad Fahimi1, Leila Torkzadeh1, Dumitru Baleanu2,3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1495-1514, 2022, DOI:10.32604/cmc.2022.024406

    Abstract The novel Coronavirus COVID-19 emerged in Wuhan, China in December 2019. COVID-19 has rapidly spread among human populations and other mammals. The outbreak of COVID-19 has become a global challenge. Mathematical models of epidemiological systems enable studying and predicting the potential spread of disease. Modeling and predicting the evolution of COVID-19 epidemics in near real-time is a scientific challenge, this requires a deep understanding of the dynamics of pandemics and the possibility that the diffusion process can be completely random. In this paper, we develop and analyze a model to simulate the Coronavirus transmission dynamics… More >

  • Open Access

    ARTICLE

    Optimal Deep Learning Based Inception Model for Cervical Cancer Diagnosis

    Tamer AbuKhalil1, Bassam A. Y. Alqaralleh2,*, Ahmad H. Al-Omari3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 57-71, 2022, DOI:10.32604/cmc.2022.024367

    Abstract Prevention of cervical cancer becomes essential and is carried out by the use of Pap smear images. Pap smear test analysis is laborious and tiresome work performed visually using a cytopathologist. Therefore, automated cervical cancer diagnosis using automated methods are necessary. This paper designs an optimal deep learning based Inception model for cervical cancer diagnosis (ODLIM-CCD) using pap smear images. The proposed ODLIM-CCD technique incorporates median filtering (MF) based pre-processing to discard the noise and Otsu model based segmentation process. Besides, deep convolutional neural network (DCNN) based Inception with Residual Network (ResNet) v2 model is More >

  • Open Access

    ARTICLE

    Efficiency Effect of Obstacle Margin on Line-of-Sight in Wireless Networks

    Murad A. A. Almekhlafi1, Taiseer Abdalla Elfadil Eisa2, Fahd N. Al-Wesabi3,4, Abdelzahir Abdelmaboud5, Manar Ahmed Hamza6,*, Abdelwahed Motwakel6, Ishfaq Yaseen6, Mohammed Rizwanullah6

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 227-242, 2022, DOI:10.32604/cmc.2022.024356

    Abstract Line-of-sight clarity and assurance are essential because they are considered the golden rule in wireless network planning, allowing the direct propagation path to connect the transmitter and receiver and retain the strength of the signal to be received. Despite the increasing literature on the line of sight with different scenarios, no comprehensive study focuses on the multiplicity of parameters and basic concepts that must be taken into account when studying such a topic as it affects the results and their accuracy. Therefore, this research aims to find limited values that ensure that the signal reaches… More >

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