Haya Mesfer Alshahrani¹, Faisal S. Alsubaei², Taiseer Abdalla Elfadil Eisa³, Mohamed K. Nour⁴, Manar Ahmed Hamza^5,*, Abdelwahed Motwakel⁵, Abu Sarwar Zamani⁵, Ishfaq Yaseen⁵

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1557-1570, 2022, DOI:10.32604/cmc.2022.027135 - 18 May 2022

Abstract The increasing quantity of sensitive and personal data being gathered by data controllers has raised the security needs in the cloud environment. Cloud computing (CC) is used for storing as well as processing data. Therefore, security becomes important as the CC handles massive quantity of outsourced, and unprotected sensitive data for public access. This study introduces a novel chaotic chimp optimization with machine learning enabled information security (CCOML-IS) technique on cloud environment. The proposed CCOML-IS technique aims to accomplish maximum security in the CC environment by the identification of intrusions or anomalies in the network.… More >

Hanan Abdullah Mengash¹, Radwa Marzouk¹, Siwar Ben Haj Hassine², Anwer Mustafa Hilal^3,*, Ishfaq Yaseen³, Abdelwahed Motwakel³

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 327-342, 2022, DOI:10.32604/cmc.2022.026464 - 18 May 2022

Abstract Artificial intelligence (AI) techniques have received significant attention among research communities in the field of networking, image processing, natural language processing, robotics, etc. At the same time, a major problem in wireless sensor networks (WSN) is node localization, which aims to identify the exact position of the sensor nodes (SN) using the known position of several anchor nodes. WSN comprises a massive number of SNs and records the position of the nodes, which becomes a tedious process. Besides, the SNs might be subjected to node mobility and the position alters with time. So, a precise… More >

Phan Nguyen Ky Phuc¹, Nguyen Van Thanh^2,*, Duong Bao Tram¹

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5165-5178, 2022, DOI:10.32604/cmc.2022.027967 - 21 April 2022

Abstract The cross-docking is a very important subject in logistics and supply chain managements. According to the definition, cross-docking is a process dealing with transhipping inventory, in which goods and products are unloaded from an inbound truck and process through a flow-center to be directly loaded onto an outbound truck. Cross-docking is favored due to its advantages in reducing the material handing cost, the needs to store the product in warehouse, as well decreasing the labor cost by eliminating packaging, storing, pick-location and order picking. In cross-docking, products can be consolidated and transported as a full… More >

Souad Larabi-Marie-Sainte¹, Eatedal Alabdulkreem², Mohammad Alamgeer³, Mohamed K Nour⁴, Anwer Mustafa Hilal^5,*, Mesfer Al Duhayyim⁶, Abdelwahed Motwakel⁵, Ishfaq Yaseen⁵

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4589-4601, 2022, DOI:10.32604/cmc.2022.027922 - 21 April 2022

Abstract Electroencephalography (EEG) eye state classification becomes an essential tool to identify the cognitive state of humans. It can be used in several fields such as motor imagery recognition, drug effect detection, emotion categorization, seizure detection, etc. With the latest advances in deep learning (DL) models, it is possible to design an accurate and prompt EEG EyeState classification problem. In this view, this study presents a novel compact bat algorithm with deep learning model for biomedical EEG EyeState classification (CBADL-BEESC) model. The major intention of the CBADL-BEESC technique aims to categorize the presence of EEG EyeState. More >

Esam A. AlQaralleh¹, Fahad Aldhaban², Halah Nasseif², Bassam A.Y. Alqaralleh^2,*, Tamer AbuKhalil³

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5727-5740, 2022, DOI:10.32604/cmc.2022.026780 - 21 April 2022

Abstract Recent technological advancements have been used to improve the quality of living in smart cities. At the same time, automated detection of vehicles can be utilized to reduce crime rate and improve public security. On the other hand, the automatic identification of vehicle license plate (LP) character becomes an essential process to recognize vehicles in real time scenarios, which can be achieved by the exploitation of optimal deep learning (DL) approaches. In this article, a novel hybrid metaheuristic optimization based deep learning model for automated license plate character recognition (HMODL-ALPCR) technique has been presented for… More >

Bassam A. Y. Alqaralleh^1,*, Fahad Aldhaban¹, Esam A. AlQarallehs², Ahmad H. Al-Omari³

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4691-4707, 2022, DOI:10.32604/cmc.2022.026556 - 21 April 2022

Abstract Cyber-attacks on cyber-physical systems (CPSs) resulted to sensing and actuation misbehavior, severe damage to physical object, and safety risk. Machine learning (ML) models have been presented to hinder cyberattacks on the CPS environment; however, the non-existence of labelled data from new attacks makes their detection quite interesting. Intrusion Detection System (IDS) is a commonly utilized to detect and classify the existence of intrusions in the CPS environment, which acts as an important part in secure CPS environment. Latest developments in deep learning (DL) and explainable artificial intelligence (XAI) stimulate new IDSs to manage cyberattacks with… More >

Masoud Alajmi¹, Mohamed K. Nour², Siwar Ben Haj Hassine³, Mimouna Abdullah Alkhonaini⁴, Manar Ahmed Hamza^5,*, Ishfaq Yaseen⁵, Abu Sarwar Zamani⁵, Mohammed Rizwanullah⁵

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5499-5513, 2022, DOI:10.32604/cmc.2022.026187 - 21 April 2022

Abstract Recently, cyber physical system (CPS) has gained significant attention which mainly depends upon an effective collaboration with computation and physical components. The greatly interrelated and united characteristics of CPS resulting in the development of cyber physical energy systems (CPES). At the same time, the rising ubiquity of wireless sensor networks (WSN) in several application areas makes it a vital part of the design of CPES. Since security and energy efficiency are the major challenging issues in CPES, this study offers an energy aware secure cyber physical systems with clustered wireless sensor networks using metaheuristic algorithms… More >

Ala’ A. Eshmawi¹, Suliman A. Alsuhibany², Sayed Abdel-Khalek³, Romany F. Mansour^4,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 4173-4184, 2022, DOI:10.32604/cmc.2022.028008 - 29 March 2022

Abstract Digital image security is a fundamental and tedious process on shared communication channels. Several methods have been employed for accomplishing security on digital image transmission, such as encryption, steganography, and watermarking. Image stenography and encryption are commonly used models to achieve improved security. Besides, optimal pixel selection process (OPSP) acts as a vital role in the encryption process. With this motivation, this study designs a new competitive swarm optimization with encryption based stenographic technique for digital image security, named CSOES-DIS technique. The proposed CSOES-DIS model aims to encrypt the secret image prior to the embedding More >

Areej A. Malibari¹, Siwar Ben Haj Hassine², Abdelwahed Motwakel³, Manar Ahmed Hamza^3,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2859-2875, 2022, DOI:10.32604/cmc.2022.026338 - 29 March 2022

Abstract Atherosclerosis diagnosis is an inarticulate and complicated cognitive process. Researches on medical diagnosis necessitate maximum accuracy and performance to make optimal clinical decisions. Since the medical diagnostic outcomes need to be prompt and accurate, the recently developed artificial intelligence (AI) and deep learning (DL) models have received considerable attention among research communities. This study develops a novel Metaheuristics with Deep Learning Empowered Biomedical Atherosclerosis Disease Diagnosis and Classification (MDL-BADDC) model. The proposed MDL-BADDC technique encompasses several stages of operations such as pre-processing, feature selection, classification, and parameter tuning. Besides, the proposed MDL-BADDC technique designs a More >

Thavavel Vaiyapuri¹, K. Priyadarshini², A. Hemlathadhevi³, M. Dhamodaran⁴, Ashit Kumar Dutta⁵, Irina V. Pustokhina^6,*, Denis A. Pustokhin⁷

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2429-2444, 2022, DOI:10.32604/cmc.2022.026204 - 29 March 2022

Abstract Due to global financial crisis, risk management has received significant attention to avoid loss and maximize profit in any business. Since the financial crisis prediction (FCP) process is mainly based on data driven decision making and intelligent models, artificial intelligence (AI) and machine learning (ML) models are widely utilized. This article introduces an intelligent feature selection with deep learning based financial risk assessment model (IFSDL-FRA). The proposed IFSDL-FRA technique aims to determine the financial crisis of a company or enterprise. In addition, the IFSDL-FRA technique involves the design of new water strider optimization algorithm based More >