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  • Open Access

    ARTICLE

    Phishing Website URL’s Detection Using NLP and Machine Learning Techniques

    Dinesh Kalla1,*, Sivaraju Kuraku2

    Journal on Artificial Intelligence, Vol.5, pp. 145-162, 2023, DOI:10.32604/jai.2023.043366

    Abstract Phishing websites present a severe cybersecurity risk since they can lead to financial losses, data breaches, and user privacy violations. This study uses machine learning approaches to solve the problem of phishing website detection. Using artificial intelligence, the project aims to provide efficient techniques for locating and thwarting these dangerous websites. The study goals were attained by performing a thorough literature analysis to investigate several models and methods often used in phishing website identification. Logistic Regression, K-Nearest Neighbors, Decision Trees, Random Forests, Support Vector Classifiers, Linear Support Vector Classifiers, and Naive Bayes were all used in the inquiry. This research… More >

  • Open Access

    ARTICLE

    ENHANCEMENT OF FRESH WATER PRODUCTION ON TRIANGULAR PYRAMID SOLAR STILL USING PHASE CHANGE MATERIAL AS STORAGE MATERIAL

    Ravishankar Sathyamurthya,*, P.K. Nagarajanb, Hyacinth J. Kennadya, T.S. Ravikumara, V. Paulsonc, Amimul Ahsand

    Frontiers in Heat and Mass Transfer, Vol.5, pp. 1-5, 2014, DOI:10.5098/hmt.5.3

    Abstract This paper presents the method of improvement of enhancing the performance of triangular pyramid solar still with and without latent heat energy storage. For comparing the productivity of solar still with and without LHTESS a solar still is designed, fabricated. Experiments are conducted in hot and humid climate of Chennai, India. Paraffin wax is used as LHTESS due to its feasible general and economic properties. The hourly productivity is slightly higher in case of solar still without LHTESS during sunny days. There is an increase of about 35% in production of fresh water with LHTESS than that of solar still… More >

  • Open Access

    ARTICLE

    Assessing the Efficacy of Improved Learning in Hourly Global Irradiance Prediction

    Abdennasser Dahmani1, Yamina Ammi2, Nadjem Bailek3,4,*, Alban Kuriqi5,6, Nadhir Al-Ansari7,*, Salah Hanini2, Ilhami Colak8, Laith Abualigah9,10,11,12,13,14, El-Sayed M. El-kenawy15

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2579-2594, 2023, DOI:10.32604/cmc.2023.040625

    Abstract Increasing global energy consumption has become an urgent problem as natural energy sources such as oil, gas, and uranium are rapidly running out. Research into renewable energy sources such as solar energy is being pursued to counter this. Solar energy is one of the most promising renewable energy sources, as it has the potential to meet the world’s energy needs indefinitely. This study aims to develop and evaluate artificial intelligence (AI) models for predicting hourly global irradiation. The hyperparameters were optimized using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton training algorithm and STATISTICA software. Data from two stations in Algeria with different climatic… More >

  • Open Access

    ARTICLE

    Optimizing Power Allocation for D2D Communication with URLLC under Rician Fading Channel: A Learning-to-Optimize Approach

    Owais Muhammad1, Hong Jiang1,*, Mushtaq Muhammad Umer1, Bilal Muhammad2, Naeem Muhammad Ahtsam3

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3193-3212, 2023, DOI:10.32604/iasc.2023.041232

    Abstract To meet the high-performance requirements of fifth-generation (5G) and sixth-generation (6G) wireless networks, in particular, ultra-reliable and low-latency communication (URLLC) is considered to be one of the most important communication scenarios in a wireless network. In this paper, we consider the effects of the Rician fading channel on the performance of cooperative device-to-device (D2D) communication with URLLC. For better performance, we maximize and examine the system’s minimal rate of D2D communication. Due to the interference in D2D communication, the problem of maximizing the minimum rate becomes non-convex and difficult to solve. To solve this problem, a learning-to-optimize-based algorithm is proposed… More >

  • Open Access

    ARTICLE

    Modelling an Efficient URL Phishing Detection Approach Based on a Dense Network Model

    A. Aldo Tenis*, R. Santhosh

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2625-2641, 2023, DOI:10.32604/csse.2023.036626

    Abstract The social engineering cyber-attack is where culprits mislead the users by getting the login details which provides the information to the evil server called phishing. The deep learning approaches and the machine learning are compared in the proposed system for presenting the methodology that can detect phishing websites via Uniform Resource Locator (URLs) analysis. The legal class is composed of the home pages with no inclusion of login forms in most of the present modern solutions, which deals with the detection of phishing. Contrarily, the URLs in both classes from the login page due, considering the representation of a real… More >

  • Open Access

    ARTICLE

    Medical Image Fusion Based on Anisotropic Diffusion and Non-Subsampled Contourlet Transform

    Bhawna Goyal1,*, Ayush Dogra2, Rahul Khoond1, Dawa Chyophel Lepcha1, Vishal Goyal3, Steven L. Fernandes4

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 311-327, 2023, DOI:10.32604/cmc.2023.038398

    Abstract The synthesis of visual information from multiple medical imaging inputs to a single fused image without any loss of detail and distortion is known as multimodal medical image fusion. It improves the quality of biomedical images by preserving detailed features to advance the clinical utility of medical imaging meant for the analysis and treatment of medical disorders. This study develops a novel approach to fuse multimodal medical images utilizing anisotropic diffusion (AD) and non-subsampled contourlet transform (NSCT). First, the method employs anisotropic diffusion for decomposing input images to their base and detail layers to coarsely split two features of input… More >

  • Open Access

    ARTICLE

    Image Fusion Based on NSCT and Sparse Representation for Remote Sensing Data

    N. A. Lawrance*, T. S. Shiny Angel

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3439-3455, 2023, DOI:10.32604/csse.2023.030311

    Abstract The practice of integrating images from two or more sensors collected from the same area or object is known as image fusion. The goal is to extract more spatial and spectral information from the resulting fused image than from the component images. The images must be fused to improve the spatial and spectral quality of both panchromatic and multispectral images. This study provides a novel picture fusion technique that employs L0 smoothening Filter, Non-subsampled Contour let Transform (NSCT) and Sparse Representation (SR) followed by the Max absolute rule (MAR). The fusion approach is as follows: first, the multispectral and panchromatic… More >

  • Open Access

    ARTICLE

    Analysis and Economic Evaluation of Hourly Operation Strategy Based on MSW Classification and LNG Multi-Generation System

    Xueqing Lu, Yuetao Shi*, Jinsong Li

    Energy Engineering, Vol.120, No.6, pp. 1325-1352, 2023, DOI:10.32604/ee.2023.026142

    Abstract In this study, a model of combined cooling, heating and power system with municipal solid waste (MSW) and liquefied natural gas (LNG) as energy sources was proposed and developed based on the energy demand of a large community, and MSW was classified and utilized. The system operated by determining power by heating load, and measures were taken to reduce operating costs by purchasing and selling LNG, natural gas (NG), cooling, heating, and power. Based on this system model, three operation strategies were proposed based on whether MSW was classified and the length of kitchen waste fermentation time, and each strategy… More > Graphic Abstract

    Analysis and Economic Evaluation of Hourly Operation Strategy Based on MSW Classification and LNG Multi-Generation System

  • Open Access

    ARTICLE

    Machine Learning Techniques for Detecting Phishing URL Attacks

    Diana T. Mosa1,2, Mahmoud Y. Shams3,*, Amr A. Abohany2, El-Sayed M. El-kenawy4, M. Thabet5

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1271-1290, 2023, DOI:10.32604/cmc.2023.036422

    Abstract Cyber Attacks are critical and destructive to all industry sectors. They affect social engineering by allowing unapproved access to a Personal Computer (PC) that breaks the corrupted system and threatens humans. The defense of security requires understanding the nature of Cyber Attacks, so prevention becomes easy and accurate by acquiring sufficient knowledge about various features of Cyber Attacks. Cyber-Security proposes appropriate actions that can handle and block attacks. A phishing attack is one of the cybercrimes in which users follow a link to illegal websites that will persuade them to divulge their private information. One of the online security challenges… More >

  • Open Access

    ARTICLE

    Malicious URL Classification Using Artificial Fish Swarm Optimization and Deep Learning

    Anwer Mustafa Hilal1,2,*, Aisha Hassan Abdalla Hashim1, Heba G. Mohamed3, Mohamed K. Nour4, Mashael M. Asiri5, Ali M. Al-Sharafi6, Mahmoud Othman7, Abdelwahed Motwakel2

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 607-621, 2023, DOI:10.32604/cmc.2023.031371

    Abstract Cybersecurity-related solutions have become familiar since it ensures security and privacy against cyberattacks in this digital era. Malicious Uniform Resource Locators (URLs) can be embedded in email or Twitter and used to lure vulnerable internet users to implement malicious data in their systems. This may result in compromised security of the systems, scams, and other such cyberattacks. These attacks hijack huge quantities of the available data, incurring heavy financial loss. At the same time, Machine Learning (ML) and Deep Learning (DL) models paved the way for designing models that can detect malicious URLs accurately and classify them. With this motivation,… More >

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