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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 - 18 December 2023

    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 More >

  • Open Access

    ARTICLE

    Research on the Follow-Up Control Strategy of Biaxial Fatigue Test of Wind Turbine Blade Based on Electromagnetic Excitation

    Wenzhe Guo1, Leian Zhang1,*, Chao Lv2, Weisheng Liu3, Jiabin Tian2

    Energy Engineering, Vol.120, No.10, pp. 2307-2323, 2023, DOI:10.32604/ee.2023.030029 - 28 September 2023

    Abstract Aiming at the drift problem that the tracking control of the actual load relative to the target load during the electromagnetic excitation biaxial fatigue test of wind turbine blades is easy to drift, a biaxial fatigue testing machine for electromagnetic excitation is designed, and the following strategy of the actual load and the target load is studied. A Fast Transversal Recursive Least Squares algorithm based on fuzzy logic (Fuzzy FTRLS) is proposed to develop a fatigue loading following dynamic strategy, which adjusts the forgetting factor in the algorithm through fuzzy logic to overcome the contradiction More >

  • Open Access

    ARTICLE

    Improving QoS Using Mobility-Based Optimized Multipath Routing Protocol in MANET

    S. J. Sangeetha1,*, T. Rajendran2

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1169-1181, 2023, DOI:10.32604/csse.2023.033392 - 20 January 2023

    Abstract Mobile Ad-hoc Networks (MANETs) connect numerous nodes to communicate data from the sender node to the target node. Due to the lack of an infrastructure network, mobile nodes communicate through wireless without an access point. MANET does not have a centralized controller and has a dynamic network topology, which increases link failure and energy consumption resulting in excessive path delay, loss of Quality of service (QoS), and reduced throughput during data communication. Congestion is a significant problem when the QoS of the link carrying the data is degraded. Routing is one of the vital challenges… More >

  • Open Access

    ARTICLE

    Impulsive Noise Cancellation in OFDM System Using Low Density Parity Check

    Attia Irum1, Abdul Muiz Fayyaz1, Sara Ayub2, Mudassar Raza3, Majed Alhaisoni4, Muhammad Attique Khan5, Abdullah Alqahtani6, Heebum Kim7, Byeong-Gwon Kang7,*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1265-1276, 2023, DOI:10.32604/csse.2023.032861 - 20 January 2023

    Abstract An effective communication application necessitates the cancellation of Impulsive Noise (IN) from Orthogonal Frequency Division Multiplexing (OFDM), which is widely used for wireless applications due to its higher data rate and greater spectral efficiency. The OFDM system is typically corrupted by Impulsive Noise, which is an unwanted short-duration pulse with random amplitude and duration. Impulsive noise is created by humans and has non-Gaussian characteristics, causing problems in communication systems such as high capacity loss and poor error rate performance. Several techniques have been introduced in the literature to solve this type of problem, but they… More >

  • Open Access

    ARTICLE

    Phish Block: A Blockchain Framework for Phish Detection in Cloud

    R. N. Karthika*, C. Valliyammai, M. Naveena

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 777-795, 2023, DOI:10.32604/csse.2023.024086 - 01 June 2022

    Abstract The data in the cloud is protected by various mechanisms to ensure security aspects and user’s privacy. But, deceptive attacks like phishing might obtain the user’s data and use it for malicious purposes. In Spite of much technological advancement, phishing acts as the first step in a series of attacks. With technological advancements, availability and access to the phishing kits has improved drastically, thus making it an ideal tool for the hackers to execute the attacks. The phishing cases indicate use of foreign characters to disguise the original Uniform Resource Locator (URL), typosquatting the popular… More >

  • Open Access

    ARTICLE

    Enhancing Detection of Malicious URLs Using Boosting and Lexical Features

    Mohammad Atrees*, Ashraf Ahmad, Firas Alghanim

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1405-1422, 2022, DOI:10.32604/iasc.2022.020229 - 09 October 2021

    Abstract A malicious URL is a link that is created to spread spams, phishing, malware, ransomware, spyware, etc. A user may download malware that can adversely affect the computer by clicking on an infected URL, or might be convinced to provide confidential information to a fraudulent website causing serious losses. These threats must be identified and handled in a decent time and in an effective way. Detection is traditionally done through the blacklist usage method, which relies on keyword matching with previously known malicious domain names stored in a repository. This method is fast and easy… More >

  • Open Access

    ARTICLE

    Adversarial Attacks on Featureless Deep Learning Malicious URLs Detection

    Bader Rasheed1, Adil Khan1, S. M. Ahsan Kazmi2, Rasheed Hussain2, Md. Jalil Piran3,*, Doug Young Suh4

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 921-939, 2021, DOI:10.32604/cmc.2021.015452 - 22 March 2021

    Abstract Detecting malicious Uniform Resource Locators (URLs) is crucially important to prevent attackers from committing cybercrimes. Recent researches have investigated the role of machine learning (ML) models to detect malicious URLs. By using ML algorithms, first, the features of URLs are extracted, and then different ML models are trained. The limitation of this approach is that it requires manual feature engineering and it does not consider the sequential patterns in the URL. Therefore, deep learning (DL) models are used to solve these issues since they are able to perform featureless detection. Furthermore, DL models give better… More >

  • Open Access

    ARTICLE

    Prediction of Time Series Empowered with a Novel SREKRLS Algorithm

    Bilal Shoaib1, Yasir Javed2, Muhammad Adnan Khan3,*, Fahad Ahmad4, Rizwan Majeed5, Muhammad Saqib Nawaz1, Muhammad Adeel Ashraf6, Abid Iqbal2, Muhammad Idrees7

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1413-1427, 2021, DOI:10.32604/cmc.2021.015099 - 05 February 2021

    Abstract For the unforced dynamical non-linear statespace model, a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this article. The proposed algorithm lends itself towards the parallel implementation as in the FPGA systems. With the help of an ortho-normal triangularization method, which relies on numerically stable givens rotation, matrix inversion causes a computational burden, is reduced. Matrix computation possesses many excellent numerical properties such as singularity, symmetry, skew symmetry, and triangularity is achieved by using this algorithm. The proposed method is validated for the prediction of stationary and… More >

  • Open Access

    ARTICLE

    A Convolution-Based System for Malicious URLs Detection

    Chaochao Luo1, Shen Su2, *, Yanbin Sun2, Qingji Tan3, Meng Han4, Zhihong Tian2, *

    CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 399-411, 2020, DOI:10.32604/cmc.2020.06507

    Abstract Since the web service is essential in daily lives, cyber security becomes more and more important in this digital world. Malicious Uniform Resource Locator (URL) is a common and serious threat to cybersecurity. It hosts unsolicited content and lure unsuspecting users to become victim of scams, such as theft of private information, monetary loss, and malware installation. Thus, it is imperative to detect such threats. However, traditional approaches for malicious URLs detection that based on the blacklists are easy to be bypassed and lack the ability to detect newly generated malicious URLs. In this paper, More >

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