Mohammad Atrees^*, Ashraf Ahmad, Firas Alghanim

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

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 to implement, with the advantage… More >

Zeyad Ghaleb Al-Mekhlafi¹, Badiea Abdulkarem Mohammed^1,2,*, Mohammed Al-Sarem³, Faisal Saeed³, Tawfik Al-Hadhrami⁴, Mohammad T. Alshammari¹, Abdulrahman Alreshidi¹, Talal Sarheed Alshammari¹

Computer Systems Science and Engineering, Vol.41, No.1, pp. 109-125, 2022, DOI:10.32604/csse.2022.020414

Abstract Phishing attacks are security attacks that do not affect only individuals’ or organizations’ websites but may affect Internet of Things (IoT) devices and networks. IoT environment is an exposed environment for such attacks. Attackers may use thingbots software for the dispersal of hidden junk emails that are not noticed by users. Machine and deep learning and other methods were used to design detection methods for these attacks. However, there is still a need to enhance detection accuracy. Optimization of an ensemble classification method for phishing website (PW) detection is proposed in this study. A Genetic Algorithm (GA) was used for… More >

A. Arunkumar^1,*, D. Surendran²

Computer Systems Science and Engineering, Vol.41, No.1, pp. 389-404, 2022, DOI:10.32604/csse.2022.020256

Abstract Difficulty in communicating and interacting with other people are mainly due to the neurological disorder called autism spectrum disorder (ASD) diseases. These diseases can affect the nerves at any stage of the human being in childhood, adolescence, and adulthood. ASD is known as a behavioral disease due to the appearances of symptoms over the first two years that continue until adulthood. Most of the studies prove that the early detection of ASD helps improve the behavioral characteristics of patients with ASD. The detection of ASD is a very challenging task among various researchers. Machine learning (ML) algorithms still act very… More >

R. Siva Subramanian^1,*, D. Prabha²

Computer Systems Science and Engineering, Vol.41, No.1, pp. 339-355, 2022, DOI:10.32604/csse.2022.020043

Abstract Executing customer analysis in a systemic way is one of the possible solutions for each enterprise to understand the behavior of consumer patterns in an efficient and in-depth manner. Further investigation of customer patterns helps the firm to develop efficient decisions and in turn, helps to optimize the enterprise’s business and maximizes consumer satisfaction correspondingly. To conduct an effective assessment about the customers, Naive Bayes(also called Simple Bayes), a machine learning model is utilized. However, the efficacious of the simple Bayes model is utterly relying on the consumer data used, and the existence of uncertain and redundant attributes in the… More >

Asma A. Alhashmi^*, Abdulbasit A. Darem

Computer Systems Science and Engineering, Vol.41, No.1, pp. 241-254, 2022, DOI:10.32604/csse.2022.020023

Abstract Due to the proliferation of internet-enabled smartphones, many people, particularly young people in Arabic society, have widely adopted social media platforms as a primary means of communication, interaction and friendship making. The technological advances in smartphones and communication have enabled young people to keep in touch and form huge social networks from all over the world. However, such networks expose young people to cyberbullying and offensive content that puts their safety and emotional well-being at serious risk. Although, many solutions have been proposed to automatically detect cyberbullying, most of the existing solutions have been designed for English speaking consumers. The… More >

Jae-Hyun Ro¹, Jong-Gyu Ha², Woon-Sang Lee², Young-Hwan You³, Hyoung-Kyu Song^2,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3625-3636, 2022, DOI:10.32604/cmc.2022.020596

Abstract This paper proposes the multiple-input multiple-output (MIMO) detection scheme by using the deep neural network (DNN) based ensemble machine learning for higher error performance in wireless communication systems. For the MIMO detection based on the ensemble machine learning, all learning models for the DNN are generated in offline and the detection is performed in online by using already learned models. In the offline learning, the received signals and channel coefficients are set to input data, and the labels which correspond to transmit symbols are set to output data. In the online learning, the perfectly learned models are used for signal… More >

D. Stalin David^1,*, S. Arun Mozhi Selvi², S. Sivaprakash³, P. Vishnu Raja⁴, Dilip Kumar Sharma⁵, Pankaj Dadheech⁶, Sudhakar Sengan⁷

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2563-2579, 2022, DOI:10.32604/cmc.2022.020059

Abstract Irretrievable loss of vision is the predominant result of Glaucoma in the retina. Recently, multiple approaches have paid attention to the automatic detection of glaucoma on fundus images. Due to the interlace of blood vessels and the herculean task involved in glaucoma detection, the exactly affected site of the optic disc of whether small or big size cup, is deemed challenging. Spatially Based Ellipse Fitting Curve Model (SBEFCM) classification is suggested based on the Ensemble for a reliable diagnosis of Glaucoma in the Optic Cup (OC) and Optic Disc (OD) boundary correspondingly. This research deploys the Ensemble Convolutional Neural Network… More >

Nataliya Shakhovska¹, Nataliia Melnykova^1,*, Valentyna Chopiyak², Michal Gregus ml³

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3969-3984, 2022, DOI:10.32604/cmc.2022.019882

Abstract The paper reports three new ensembles of supervised learning predictors for managing medical insurance costs. The open dataset is used for data analysis methods development. The usage of artificial intelligence in the management of financial risks will facilitate economic wear time and money and protect patients’ health. Machine learning is associated with many expectations, but its quality is determined by choosing a good algorithm and the proper steps to plan, develop, and implement the model. The paper aims to develop three new ensembles for individual insurance costs prediction to provide high prediction accuracy. Pierson coefficient and Boruta algorithm are used… More >

Oday A. Hassen^1,*, Nur Azman Abu¹, Zaheera Zainal Abidin¹, Saad M. Darwish²

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2453-2469, 2022, DOI:10.32604/cmc.2022.019125

Abstract A robust smile recognition system could be widely used for many real-world applications. Classification of a facial smile in an unconstrained setting is difficult due to the invertible and wide variety in face images. In this paper, an adaptive model for smile expression classification is suggested that integrates a fast features extraction algorithm and cascade classifiers. Our model takes advantage of the intrinsic association between face detection, smile, and other face features to alleviate the over-fitting issue on the limited training set and increase classification results. The features are extracted taking into account to exclude any unnecessary coefficients in the… More >

Sultan Noman Qasem^1,2, Mohammed Al-Sarem^3,4, Faisal Saeed^3,*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1721-1747, 2022, DOI:10.32604/cmc.2022.018972

Abstract Rumors regarding epidemic diseases such as COVID 19, medicines and treatments, diagnostic methods and public emergencies can have harmful impacts on health and political, social and other aspects of people’s lives, especially during emergency situations and health crises. With huge amounts of content being posted to social media every second during these situations, it becomes very difficult to detect fake news (rumors) that poses threats to the stability and sustainability of the healthcare sector. A rumor is defined as a statement for which truthfulness has not been verified. During COVID 19, people found difficulty in obtaining the most truthful news… More >