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  • Open Access

    ARTICLE

    A Secure NDN Framework for Internet of Things Enabled Healthcare

    Syed Sajid Ullah1, Saddam Hussain1,*, Abdu Gumaei2,3, Hussain AlSalman2,4

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 223-240, 2021, DOI:10.32604/cmc.2021.014413

    Abstract Healthcare is a binding domain for the Internet of Things (IoT) to automate healthcare services for sharing and accumulation patient records at anytime from anywhere through the Internet. The current IP-based Internet architecture suffers from latency, mobility, location dependency, and security. The Named Data Networking (NDN) has been projected as a future internet architecture to cope with the limitations of IP-based Internet. However, the NDN infrastructure does not have a secure framework for IoT healthcare information. In this paper, we proposed a secure NDN framework for IoT-enabled Healthcare (IoTEH). In the proposed work, we adopt the services of Identity-Based Signcryption… More >

  • Open Access

    ARTICLE

    Automatic Segmentation of Liver from Abdominal Computed Tomography Images Using Energy Feature

    Prabakaran Rajamanickam1, Shiloah Elizabeth Darmanayagam1,*, Sunil Retmin Raj Cyril Raj2

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 709-722, 2021, DOI:10.32604/cmc.2021.014347

    Abstract Liver Segmentation is one of the challenging tasks in detecting and classifying liver tumors from Computed Tomography (CT) images. The segmentation of hepatic organ is more intricate task, owing to the fact that it possesses a sizeable quantum of vascularization. This paper proposes an algorithm for automatic seed point selection using energy feature for use in level set algorithm for segmentation of liver region in CT scans. The effectiveness of the method can be determined when used in a model to classify the liver CT images as tumorous or not. This involves segmentation of the region of interest (ROI) from… More >

  • Open Access

    ARTICLE

    Enhancing Network Intrusion Detection Model Using Machine Learning Algorithms

    Nancy Awadallah Awad*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 979-990, 2021, DOI:10.32604/cmc.2021.014307

    Abstract After the digital revolution, large quantities of data have been generated with time through various networks. The networks have made the process of data analysis very difficult by detecting attacks using suitable techniques. While Intrusion Detection Systems (IDSs) secure resources against threats, they still face challenges in improving detection accuracy, reducing false alarm rates, and detecting the unknown ones. This paper presents a framework to integrate data mining classification algorithms and association rules to implement network intrusion detection. Several experiments have been performed and evaluated to assess various machine learning classifiers based on the KDD99 intrusion dataset. Our study focuses… More >

  • Open Access

    ARTICLE

    Securing Technique Using Pattern-Based LSB Audio Steganography and Intensity-Based Visual Cryptography

    Pranati Rakshit1, Sreeparna Ganguly1, Souvik Pal2, Ayman A. Aly3, Dac-Nhuong Le4,5,*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1207-1224, 2021, DOI:10.32604/cmc.2021.014293

    Abstract With the increasing need of sensitive or secret data transmission through public network, security demands using cryptography and steganography are becoming a thirsty research area of last few years. These two techniques can be merged and provide better security which is nowadays extremely required. The proposed system provides a novel method of information security using the techniques of audio steganography combined with visual cryptography. In this system, we take a secret image and divide it into several subparts to make more than one incomprehensible sub-images using the method of visual cryptography. Each of the sub-images is then hidden within individual… More >

  • Open Access

    ARTICLE

    AI-Enabled COVID-19 Outbreak Analysis and Prediction: Indian States vs. Union Territories

    Meenu Gupta1, Rachna Jain2, Simrann Arora2, Akash Gupta2, Mazhar Javed Awan3, Gopal Chaudhary2,*, Haitham Nobanee4,5,6

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 933-950, 2021, DOI:10.32604/cmc.2021.014221

    Abstract The COVID-19 disease has already spread to more than 213 countries and territories with infected (confirmed) cases of more than 27 million people throughout the world so far, while the numbers keep increasing. In India, this deadly disease was first detected on January 30, 2020, in a student of Kerala who returned from Wuhan. Because of India’s high population density, different cultures, and diversity, it is a good idea to have a separate analysis of each state. Hence, this paper focuses on the comprehensive analysis of the effect of COVID-19 on Indian states and Union Territories and the development of… More >

  • Open Access

    ARTICLE

    On Computing the Suitability of Non-Human Resources for Business Process Analysis

    Abid Sohail1,*, Khurram Shahzad2, P. D. D. Dominic3, Muhammad Arif Butt2, Muhammad Arif4, Muhammad Imran Tariq5

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 303-319, 2021, DOI:10.32604/cmc.2021.014201

    Abstract Business process improvement is a systematic approach used by several organizations to continuously improve their quality of service. Integral to that is analyzing the current performance of each task of the process and assigning the most appropriate resources to each task. In continuation of our previous work, we categorize resources into human and non-human resources. For instance, in the healthcare domain, human resources include doctors, nurses, and other associated staff responsible for the execution of healthcare activities; whereas the non-human resources include surgical and other equipment needed for execution. In this study, we contend that the two types of resources… More >

  • Open Access

    ARTICLE

    Security Requirement Management for Cloud-Assisted and Internet of Things—Enabled Smart City

    Muhammad Usman Tariq1, Muhammad Babar2, Mian Ahmad Jan3,4,5,*, Akmal Saeed Khattak6, Mohammad Dahman Alshehri7, Abid Yahya8

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 625-639, 2021, DOI:10.32604/cmc.2021.014165

    Abstract The world is rapidly changing with the advance of information technology. The expansion of the Internet of Things (IoT) is a huge step in the development of the smart city. The IoT consists of connected devices that transfer information. The IoT architecture permits on-demand services to a public pool of resources. Cloud computing plays a vital role in developing IoT-enabled smart applications. The integration of cloud computing enhances the offering of distributed resources in the smart city. Improper management of security requirements of cloud-assisted IoT systems can bring about risks to availability, security, performance, confidentiality, and privacy. The key reason… More >

  • Open Access

    ARTICLE

    SwCS: Section-Wise Content Similarity Approach to Exploit Scientific Big Data

    Kashif Irshad1, Muhammad Tanvir Afzal2, Sanam Shahla Rizvi3, Abdul Shahid4, Rabia Riaz5, Tae-Sun Chung6,*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 877-894, 2021, DOI:10.32604/cmc.2021.014156

    Abstract The growing collection of scientific data in various web repositories is referred to as Scientific Big Data, as it fulfills the four “V’s” of Big Data–-volume, variety, velocity, and veracity. This phenomenon has created new opportunities for startups; for instance, the extraction of pertinent research papers from enormous knowledge repositories using certain innovative methods has become an important task for researchers and entrepreneurs. Traditionally, the content of the papers are compared to list the relevant papers from a repository. The conventional method results in a long list of papers that is often impossible to interpret productively. Therefore, the need for… More >

  • Open Access

    ARTICLE

    A Weighted Spatially Constrained Finite Mixture Model for Image Segmentation

    Mohammad Masroor Ahmed1,*, Saleh Al Shehri2, Jawad Usman Arshed3, Mahmood Ul Hassan4, Muzammil Hussain5, Mehtab Afzal6

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 171-185, 2021, DOI:10.32604/cmc.2021.014141

    Abstract Spatially Constrained Mixture Model (SCMM) is an image segmentation model that works over the framework of maximum a-posteriori and Markov Random Field (MAP-MRF). It developed its own maximization step to be used within this framework. This research has proposed an improvement in the SCMM’s maximization step for segmenting simulated brain Magnetic Resonance Images (MRIs). The improved model is named as the Weighted Spatially Constrained Finite Mixture Model (WSCFMM). To compare the performance of SCMM and WSCFMM, simulated T1-Weighted normal MRIs were segmented. A region of interest (ROI) was extracted from segmented images. The similarity level between the extracted ROI and… More >

  • Open Access

    ARTICLE

    Toward the Optimization of the Region-Based P300 Speller

    A. Benabid Najjar1,*, N. AlSahly2, R. AlShamass1, M. Hosny2

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1169-1189, 2021, DOI:10.32604/cmc.2021.014140

    Abstract Technology has tremendously contributed to improving communication and facilitating daily activities. Brain-Computer Interface (BCI) study particularly emerged from the need to serve people with disabilities such as Amyotrophic Lateral Sclerosis (ALS). However, with the advancements in cost-effective electronics and computer interface equipment, the BCI study is flourishing, and the exploration of BCI applications for people without disabilities, to enhance normal functioning, is increasing. Particularly, the P300-based spellers are among the most promising applications of the BCI technology. In this context, the region-based paradigm for P300 BCI spellers was introduced in an effort to reduce the crowding effect and adjacency problem… More >

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