A. Ramachandran^1,*, K. Gayathri², Ahmed Alkhayyat³, Rami Q. Malik⁴

Computer Systems Science and Engineering, Vol.46, No.2, pp. 2177-2194, 2023, DOI:10.32604/csse.2023.034438

Abstract Cyber-physical system (CPS) is a concept that integrates every computer-driven system interacting closely with its physical environment. Internet-of-things (IoT) is a union of devices and technologies that provide universal interconnection mechanisms between the physical and digital worlds. Since the complexity level of the CPS increases, an adversary attack becomes possible in several ways. Assuring security is a vital aspect of the CPS environment. Due to the massive surge in the data size, the design of anomaly detection techniques becomes a challenging issue, and domain-specific knowledge can be applied to resolve it. This article develops an Aquila Optimizer with Parameter Tuned… More >

Sarah B. Basahel¹, Saleh Bajaba², Mohammad Yamin³, Sachi Nandan Mohanty⁴, E. Laxmi Lydia^5,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1353-1369, 2023, DOI:10.32604/cmc.2023.036453

Abstract The current advancement in cloud computing, Artificial Intelligence (AI), and the Internet of Things (IoT) transformed the traditional healthcare system into smart healthcare. Healthcare services could be enhanced by incorporating key techniques like AI and IoT. The convergence of AI and IoT provides distinct opportunities in the medical field. Fall is regarded as a primary cause of death or post-traumatic complication for the ageing population. Therefore, earlier detection of older person falls in smart homes is required to improve the survival rate of an individual or provide the necessary support. Lately, the emergence of IoT, AI, smartphones, wearables, and so… More >

Fahad F. Alruwaili^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 99-115, 2023, DOI:10.32604/cmc.2023.034752

Abstract The Internet of Things (IoT) paradigm enables end users to access networking services amongst diverse kinds of electronic devices. IoT security mechanism is a technology that concentrates on safeguarding the devices and networks connected in the IoT environment. In recent years, False Data Injection Attacks (FDIAs) have gained considerable interest in the IoT environment. Cybercriminals compromise the devices connected to the network and inject the data. Such attacks on the IoT environment can result in a considerable loss and interrupt normal activities among the IoT network devices. The FDI attacks have been effectively overcome so far by conventional threat detection… More >

Shimaa Ouf^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1213-1233, 2023, DOI:10.32604/cmc.2023.034399

Abstract The aviation industry is one of the most competitive markets. The most common approach for airline service providers is to improve passenger satisfaction. Passenger satisfaction in the aviation industry occurs when passengers’ expectations are met during flights. Airline service quality is critical in attracting new passengers and retaining existing ones. It is crucial to identify passengers’ pain points and enhance their satisfaction with the services offered. The airlines used a variety of techniques to improve service quality. They used data analysis approaches to analyze the passenger point data. These solutions have focused simply on surveys; consequently, deep-learning approaches have received… More >

Ghada Atteia¹, El-Sayed M. El-kenawy^2,3, Nagwan Abdel Samee^1,*, Mona M. Jamjoom⁴, Abdelhameed Ibrahim⁵, Abdelaziz A. Abdelhamid^6,7, Ahmad Taher Azar^8,9, Nima Khodadadi^10,11, Reham A. Ghanem¹², Mahmoud Y. Shams¹³

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1883-1900, 2023, DOI:10.32604/cmc.2023.031723

Abstract The rapid population growth results in a crucial problem in the early detection of diseases in medical research. Among all the cancers unveiled, breast cancer is considered the second most severe cancer. Consequently, an exponential rising in death cases incurred by breast cancer is expected due to the rapid population growth and the lack of resources required for performing medical diagnoses. Utilizing recent advances in machine learning could help medical staff in diagnosing diseases as they offer effective, reliable, and rapid responses, which could help in decreasing the death risk. In this paper, we propose a new algorithm for feature… More >

Mohammad Yamin¹, Saleh Bajaba², Sarah B. Basahel³, E. Laxmi Lydia^4,*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 321-336, 2023, DOI:10.32604/csse.2023.034849

Abstract Deep learning (DL) models have been useful in many computer vision, speech recognition, and natural language processing tasks in recent years. These models seem a natural fit to handle the rising number of biometric recognition problems, from cellphone authentication to airport security systems. DL approaches have recently been utilized to improve the efficiency of various biometric recognition systems. Iris recognition was considered the more reliable and accurate biometric detection method accessible. Iris recognition has been an active research region in the last few decades due to its extensive applications, from security in airports to homeland security border control. This article… More >

Mohammed Maray¹, Badriyya B. Al-onazi², Jaber S. Alzahrani³, Saeed Masoud Alshahrani^4,*, Najm Alotaibi⁵, Sana Alazwari⁶, Mahmoud Othman⁷, Manar Ahmed Hamza⁸

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5467-5482, 2023, DOI:10.32604/cmc.2023.033534

Abstract The recognition of the Arabic characters is a crucial task in computer vision and Natural Language Processing fields. Some major complications in recognizing handwritten texts include distortion and pattern variabilities. So, the feature extraction process is a significant task in NLP models. If the features are automatically selected, it might result in the unavailability of adequate data for accurately forecasting the character classes. But, many features usually create difficulties due to high dimensionality issues. Against this background, the current study develops a Sailfish Optimizer with Deep Transfer Learning-Enabled Arabic Handwriting Character Recognition (SFODTL-AHCR) model. The projected SFODTL-AHCR model primarily focuses… More >

Mohammed Alonazi¹, Mrim M. Alnfiai^2,*

Computer Systems Science and Engineering, Vol.45, No.3, pp. 3135-3150, 2023, DOI:10.32604/csse.2023.034124

Abstract Human-Computer Interaction (HCI) is a sub-area within computer science focused on the study of the communication between people (users) and computers and the evaluation, implementation, and design of user interfaces for computer systems. HCI has accomplished effective incorporation of the human factors and software engineering of computing systems through the methods and concepts of cognitive science. Usability is an aspect of HCI dedicated to guaranteeing that human–computer communication is, amongst other things, efficient, effective, and sustaining for the user. Simultaneously, Human activity recognition (HAR) aim is to identify actions from a sequence of observations on the activities of subjects and… More >

Fatma S. Alrayes¹, Najm Alotaibi², Jaber S. Alzahrani³, Sana Alazwari⁴, Areej Alhogail⁵, Ali M. Al-Sharafi⁶, Mahmoud Othman⁷, Manar Ahmed Hamza^8,*

Computer Systems Science and Engineering, Vol.45, No.3, pp. 3037-3052, 2023, DOI:10.32604/csse.2023.033970

Abstract Recent developments in computer networks and Internet of Things (IoT) have enabled easy access to data. But the government and business sectors face several difficulties in resolving cybersecurity network issues, like novel attacks, hackers, internet criminals, and so on. Presently, malware attacks and software piracy pose serious risks in compromising the security of IoT. They can steal confidential data which results in financial and reputational losses. The advent of machine learning (ML) and deep learning (DL) models has been employed to accomplish security in the IoT cloud environment. This article presents an Enhanced Artificial Gorilla Troops Optimizer with Deep Learning… More >

Anwer Mustafa Hilal^1,2,*, Aisha Hassan Abdalla Hashim¹, Heba G. Mohamed³, Lubna A. Alharbi⁴, Mohamed K. Nour⁵, Abdullah Mohamed⁶, Ahmed S. Almasoud⁷, Abdelwahed Motwakel²

Computer Systems Science and Engineering, Vol.45, No.2, pp. 2033-2047, 2023, DOI:10.32604/csse.2023.031181

Abstract Recent developments on Internet and social networking have led to the growth of aggressive language and hate speech. Online provocation, abuses, and attacks are widely termed cyberbullying (CB). The massive quantity of user generated content makes it difficult to recognize CB. Current advancements in machine learning (ML), deep learning (DL), and natural language processing (NLP) tools enable to detect and classify CB in social networks. In this view, this study introduces a spotted hyena optimizer with deep learning driven cybersecurity (SHODLCS) model for OSN. The presented SHODLCS model intends to accomplish cybersecurity from the identification of CB in the OSN.… More >