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  • Open Access

    ARTICLE

    Hyperchaos and MD5 Based Efficient Color Image Cipher

    Muhammad Samiullah1, Waqar Aslam1, Saima Sadiq2, Arif Mehmood1, Gyu Sang Choi3,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1645-1670, 2022, DOI:10.32604/cmc.2022.021019

    Abstract While designing and developing encryption algorithms for text and images, the main focus has remained on security. This has led to insufficient attention on the improvement of encryption efficiency, enhancement of hyperchaotic sequence randomness, and dynamic DNA-based S-box. In this regard, a new symmetric block cipher scheme has been proposed. It uses dynamic DNA-based S-box connected with MD5 and a hyperchaotic system to produce confusion and diffusion for encrypting color images. Our proposed scheme supports various size color images. It generates three DNA based S-boxes for substitution namely DNA_1_s-box, DNA_2_s-box and DNA_3_s-box, each of size . Next, the 4D hyperchaotic… More >

  • Open Access

    ARTICLE

    An Optimal Deep Learning for Cooperative Intelligent Transportation System

    K. Lakshmi1, Srinivas Nagineni2, E. Laxmi Lydia3, A. Francis Saviour Devaraj4, Sachi Nandan Mohanty5, Irina V. Pustokhina6,*, Denis A. Pustokhin7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 19-35, 2022, DOI:10.32604/cmc.2022.020244

    Abstract Cooperative Intelligent Transport System (C-ITS) plays a vital role in the future road traffic management system. A vital element of C-ITS comprises vehicles, road side units, and traffic command centers, which produce a massive quantity of data comprising both mobility and service-related data. For the extraction of meaningful and related details out of the generated data, data science acts as an essential part of the upcoming C-ITS applications. At the same time, prediction of short-term traffic flow is highly essential to manage the traffic accurately. Due to the rapid increase in the amount of traffic data, deep learning (DL) models… More >

  • Open Access

    ARTICLE

    Melanoma Identification Through X-ray Modality Using Inception-v3 Based Convolutional Neural Network

    Saad Awadh Alanazi*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 37-55, 2022, DOI:10.32604/cmc.2022.020118

    Abstract Melanoma, also called malignant melanoma, is a form of skin cancer triggered by an abnormal proliferation of the pigment-producing cells, which give the skin its color. Melanoma is one of the skin diseases, which is exceptionally and globally dangerous, Skin lesions are considered to be a serious disease. Dermoscopy-based early recognition and detection procedure is fundamental for melanoma treatment. Early detection of melanoma using dermoscopy images improves survival rates significantly. At the same time, well-experienced dermatologists dominate the precision of diagnosis. However, precise melanoma recognition is incredibly hard due to several factors: low contrast between lesions and surrounding skin, visual… More >

  • Open Access

    ARTICLE

    Modeling and Simulation of Two Axes Gimbal Using Fuzzy Control

    Ayman A. Aly1, Mohamed O. Elhabib2, Bassem F. Felemban1, B. Saleh1, Dac-Nhuong Le3,4,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 93-107, 2022, DOI:10.32604/cmc.2022.019681

    Abstract The application of the guided missile seeker is to provide stability to the sensor's line of sight toward a target by isolating it from the missile motion and vibration. The main objective of this paper is not only to present the physical modeling of two axes gimbal system but also to improve its performance through using fuzzy logic controlling approach. The paper is started by deriving the mathematical model for gimbals motion using Newton's second law, followed by designing the mechanical parts of model using SOLIDWORKS and converted to xml file to connect dc motors and sensors using MATLAB/SimMechanics. Then,… More >

  • Open Access

    ARTICLE

    Sustainable-Security Assessment Through a Multi Perspective Benchmarking Framework

    Ahmed Saeed Alfakeeh1, Abdulmohsen Almalawi2, Fawaz Jaber Alsolami2, Yoosef B. Abushark2, Asif Irshad Khan2,*, Adel Aboud S. Bahaddad1, Md Mottahir Alam3, Alka Agrawal4, Rajeev Kumar5, Raees Ahmad Khan4

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6011-6037, 2022, DOI:10.32604/cmc.2022.024903

    Abstract The current cyber-attack environment has put even the most protected systems at risk as the hackers are now modifying technologies to exploit even the tiniest of weaknesses and infiltrate networks. In this situation, it's critical to design and construct software that is both secure and long-lasting. While security is the most well-defined aspect of health information software systems, it is equally significant to prioritise sustainability because any health information software system will be more effective if it provides both security and sustainability to the customers at the same time. In this league, it is crucial to determine those characteristics in… More >

  • Open Access

    ARTICLE

    A Secure Three-Party Authenticated Key Exchange Protocol for Social Networks

    Vivek Kumar Sinha1, Divya Anand1,*, Fahd S. Alharithi2, Ahmed H. Almulihi2

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6293-6305, 2022, DOI:10.32604/cmc.2022.024877

    Abstract The 3PAKE (Three-Party Authenticated Key Exchange) protocol is a valuable cryptographic method that offers safe communication and permits two diverse parties to consent to a new safe meeting code using the trusted server. There have been explored numerous 3PAKE protocols earlier to create a protected meeting code between users employing the trusted server. However, existing modified 3PAKE protocols have numerous drawbacks and are incapable to provide desired secrecy against diverse attacks such as man-in-the-middle, brute-force attacks, and many others in social networks. In this article, the authors proposed an improved as well as safe 3PAKE protocol based on the hash… More >

  • Open Access

    ARTICLE

    Reinforced CNN Forensic Discriminator to Detect Document Forgery by DCGAN

    Seo-young Lim, Jeongho Cho*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6039-6051, 2022, DOI:10.32604/cmc.2022.024862

    Abstract Recently, the technology of digital image forgery based on a generative adversarial network (GAN) has considerably improved to the extent that it is difficult to distinguish it from the original image with the naked eye by compositing and editing a person's face or a specific part with the original image. Thus, much attention has been paid to digital image forgery as a social issue. Further, document forgery through GANs can completely change the meaning and context in a document, and it is difficult to identify whether the document is forged or not, which is dangerous. Nonetheless, few studies have been… More >

  • Open Access

    ARTICLE

    Estimator-Based GPS Attitude and Angular Velocity Determination

    Dah-Jing Jwo*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6107-6124, 2022, DOI:10.32604/cmc.2022.024722

    Abstract In this paper, the estimator-based Global Positioning System (GPS) attitude and angular velocity determination is presented. Outputs of the attitude estimator include the attitude angles and attitude rates or body angular velocities, depending on the design of estimator. Traditionally as a position, velocity and time sensor, the GPS also offers a free attitude-determination interferometer. GPS research and applications to the field of attitude determination using carrier phase or Doppler measurement has been extensively conducted. The raw attitude solution using the interferometry technique based on the least-squares approach is inherently noisy. The estimator such as the Kalman filter (KF) or extended… More >

  • Open Access

    ARTICLE

    Optimized Deep Learning Model for Colorectal Cancer Detection and Classification Model

    Mahmoud Ragab1,2,3,*, Khalid Eljaaly4, Maha Farouk S. Sabir5, Ehab Bahaudien Ashary6, S. M. Abo-Dahab7,8, E. M. Khalil3,9

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5751-5764, 2022, DOI:10.32604/cmc.2022.024658

    Abstract The recent developments in biological and information technologies have resulted in the generation of massive quantities of data it speeds up the process of knowledge discovery from biological systems. Due to the advancements of medical imaging in healthcare decision making, significant attention has been paid by the computer vision and deep learning (DL) models. At the same time, the detection and classification of colorectal cancer (CC) become essential to reduce the severity of the disease at an earlier stage. The existing methods are commonly based on the combination of textual features to examine the classifier results or machine learning (ML)… More >

  • Open Access

    ARTICLE

    Exploration of IoT Nodes Communication Using LoRaWAN in Forest Environment

    Anshul Sharma1, Divneet Singh Kapoor1, Anand Nayyar2,3,*, Basit Qureshi4, Kiran Jot Singh1, Khushal Thakur1

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6239-6256, 2022, DOI:10.32604/cmc.2022.024639

    Abstract The simultaneous advances in the Internet of Things (IoT), Artificial intelligence (AI) and Robotics is going to revolutionize our world in the near future. In recent years, LoRa (Long Range) wireless powered by LoRaWAN (LoRa Wide Area Network) protocol has attracted the attention of researchers for numerous applications in the IoT domain. LoRa is a low power, unlicensed Industrial, Scientific, and Medical (ISM) band-equipped wireless technology that utilizes a wide area network protocol, i.e., LoRaWAN, to incorporate itself into the network infrastructure. In this paper, we have evaluated the LoRaWAN communication protocol for the implementation of the IoT (Internet of Things)… More >

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