Navneet Bhatt¹, Jasmine Kaur², Adarsh Anand², Omar H. Alhazmi^3,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3613-3629, 2022, DOI:10.32604/cmc.2022.026554

Abstract Software developers endeavor to build their products with the least number of bugs. Despite this, many vulnerabilities are detected in software that threatens its integrity. Various automated software i.e., vulnerability scanners, are available in the market which helps detect and manage vulnerabilities in a computer, application, or a network. Hence, the choice of an appropriate vulnerability scanner is crucial to ensure efficient vulnerability management. The current work serves a dual purpose, first, to identify the key factors which affect the vulnerability discovery process in a network. The second, is to rank the popular vulnerability scanners based on the identified attributes.… More >

Bassam A. Y. Alqaralleh^1,*, Fahad Aldhaban¹, Feras Mohammed A-Matarneh², Esam A. AlQaralleh³

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3913-3927, 2022, DOI:10.32604/cmc.2022.026531

Abstract In recent years, researchers in handwriting recognition analysis relating to indigenous languages have gained significant internet among research communities. The recent developments of artificial intelligence (AI), natural language processing (NLP), and computational linguistics (CL) find useful in the analysis of regional low resource languages. Automatic lexical task participation might be elaborated to various applications in the NLP. It is apparent from the availability of effective machine recognition models and open access handwritten databases. Arabic language is a commonly spoken Semitic language, and it is written with the cursive Arabic alphabet from right to left. Arabic handwritten Character Recognition (HCR) is… More >

Romany F. Mansour^1,*, Maha M. Althobaiti²

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3945-3959, 2022, DOI:10.32604/cmc.2022.026515

Abstract Recently, the Internet of Medical Things (IoMT) has become a research hotspot due to its various applicability in medical field. However, the data analysis and management in IoMT remain challenging owing to the existence of a massive number of devices linked to the server environment, generating a massive quantity of healthcare data. In such cases, cognitive computing can be employed that uses many intelligent technologies–machine learning (ML), deep learning (DL), artificial intelligence (AI), natural language processing (NLP) and others–to comprehend data expansively. Furthermore, breast cancer (BC) has been found to be a major cause of mortality among ladies globally. Earlier… More >

Alaa Omran Almagrabi^*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3961-3983, 2022, DOI:10.32604/cmc.2022.026513

Abstract The Industrial Internet of Things (IIoT) has been growing for presentations in industry in recent years. Security for the IIoT has unavoidably become a problem in terms of creating safe applications. Due to continual needs for new functionality, such as foresight, the number of linked devices in the industrial environment increases. Certification of fewer signatories gives strong authentication solutions and prevents trustworthy third parties from being publicly certified among available encryption instruments. Hence this blockchain-based endpoint protection platform (BCEPP) has been proposed to validate the network policies and reduce overall latency in isolation or hold endpoints. A resolver supports the… More >

Abdullah Saad AL-Malaise AL-Ghamdi¹, Mahmoud Ragab^2,3,4,*, Maha Farouk S. Sabir¹, Ahmed Elhassanein^5,6, Ashraf A. Gouda⁴

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3385-3399, 2022, DOI:10.32604/cmc.2022.026477

Abstract Education acts as an important part of economic growth and improvement in human welfare. The educational sectors have transformed a lot in recent days, and Information and Communication Technology (ICT) is an effective part of the education field. Almost every action in university and college, right from the process from counselling to admissions and fee deposits has been automated. Attendance records, quiz, evaluation, mark, and grade submissions involved the utilization of the ICT. Therefore, security is essential to accomplish cybersecurity in higher security institutions (HEIs). In this view, this study develops an Automated Outlier Detection for CyberSecurity in Higher Education… More >

Khudhayr A. Rashedi^1,2,*, Mohd Tahir Ismail¹, Abdeslam Serroukh³, S. Al wadi⁴

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3835-3847, 2022, DOI:10.32604/cmc.2022.026476

Abstract We introduce a new wavelet based procedure for detecting outliers in financial discrete time series. The procedure focuses on the analysis of residuals obtained from a model fit, and applied to the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) like model, but not limited to these models. We apply the Maximal-Overlap Discrete Wavelet Transform (MODWT) to the residuals and compare their wavelet coefficients against quantile thresholds to detect outliers. Our methodology has several advantages over existing methods that make use of the standard Discrete Wavelet Transform (DWT). The series sample size does not need to be a power of 2 and the… More >

Abdullah Saad AL-Malaise AL-Ghamdi¹, Mahmoud Ragab^2,3,4,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3131-3144, 2022, DOI:10.32604/cmc.2022.026457

Abstract Education 4.0 is being authorized more and more by the design of artificial intelligence (AI) techniques. Higher education institutions (HEI) have started to utilize Internet technologies to improve the quality of the service and boost knowledge. Due to the unavailability of information technology (IT) infrastructures, HEI is vulnerable to cyberattacks. Biometric authentication can be used to authenticate a person based on biological features such as face, fingerprint, iris, and so on. This study designs a novel search and rescue optimization with deep learning based learning authentication technique for cybersecurity in higher education institutions, named SRODL-LAC technique. The proposed SRODL-LAC technique… More >

Muhammad Zubair¹, Muhammad Kashif Hanif^1,*, Eatedal Alabdulkreem², Yazeed Ghadi³, Muhammad Irfan Khan¹, Muhammad Umer Sarwar¹, Ayesha Hanif¹

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3705-3718, 2022, DOI:10.32604/cmc.2022.026408

Abstract The secondary structure of a protein is critical for establishing a link between the protein primary and tertiary structures. For this reason, it is important to design methods for accurate protein secondary structure prediction. Most of the existing computational techniques for protein structural and functional prediction are based on machine learning with shallow frameworks. Different deep learning architectures have already been applied to tackle protein secondary structure prediction problem. In this study, deep learning based models, i.e., convolutional neural network and long short-term memory for protein secondary structure prediction were proposed. The input to proposed models is amino acid sequences… More >

Abdullah S. AL-Malaise AL-Ghamdi¹, Mahmoud Ragab^2,3,4,*, Maha Farouk S. Sabir¹

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2895-2907, 2022, DOI:10.32604/cmc.2022.026405

Abstract As higher education institutions (HEIs) go online, several benefits are attained, and also it is vulnerable to several kinds of attacks. To accomplish security, this paper presents artificial intelligence based cybersecurity intrusion detection models to accomplish security. The incorporation of the strategies into business is a tendency among several distinct industries, comprising education, have recognized as game changer. Consequently, the HEIs are highly related to the requirement and knowledge of the learner, making the education procedure highly effective. Thus, artificial intelligence (AI) and machine learning (ML) models have shown significant interest in HEIs. This study designs a novel Artificial Intelligence… More >

Fariza Sabrina^1,*, Shaleeza Sohail², Farnaz Farid³, Sayka Jahan⁴, Farhad Ahamed⁵, Steven Gordon⁶

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3777-3797, 2022, DOI:10.32604/cmc.2022.026363

Abstract With increasing world population the demand of food production has increased exponentially. Internet of Things (IoT) based smart agriculture system can play a vital role in optimising crop yield by managing crop requirements in real-time. Interpretability can be an important factor to make such systems trusted and easily adopted by farmers. In this paper, we propose a novel artificial intelligence-based agriculture system that uses IoT data to monitor the environment and alerts farmers to take the required actions for maintaining ideal conditions for crop production. The strength of the proposed system is in its interpretability which makes it easy for… More >