Open Access

ARTICLE

Sohaib Manzoor¹, Hira Manzoor², Saddaf Rubab^3,4, Muhammad Attique Khan⁵, Majed Alhaisoni⁶, Abdullah Alqahtani⁷, Ye Jin Kim⁸, Byoungchol Chang^9,*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2347-2363, 2023, DOI:10.32604/cmc.2023.034044
Abstract Despite the planned installation and operations of the traditional IEEE 802.11 networks, they still experience degraded performance due to the number of inefficiencies. One of the main reasons is the received signal strength indicator (RSSI) association problem, in which the user remains connected to the access point (AP) unless the RSSI becomes too weak. In this paper, we propose a multi-criterion association (WiMA) scheme based on software defined networking (SDN) in Wi-Fi networks. An association solution based on multi-criterion such as AP load, RSSI, and channel occupancy is proposed to satisfy the quality of service (QoS). SDN having an overall… More >

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ARTICLE

Hamza Safwan¹, Zeshan Iqbal¹, Rashid Amin¹, Muhammad Attique Khan², Majed Alhaisoni³, Abdullah Alqahtani⁴, Ye Jin Kim⁵, Byoungchol Chang^6,*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2365-2381, 2023, DOI:10.32604/cmc.2023.033896
Abstract Software-defined networking (SDN) represents a paradigm shift in network traffic management. It distinguishes between the data and control planes. APIs are then used to communicate between these planes. The controller is central to the management of an SDN network and is subject to security concerns. This research shows how a deep learning algorithm can detect intrusions in SDN-based IoT networks. Overfitting, low accuracy, and efficient feature selection is all discussed. We propose a hybrid machine learning-based approach based on Random Forest and Long Short-Term Memory (LSTM). In this study, a new dataset based specifically on Software Defined Networks is used… More >

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ARTICLE

Abida Sharif¹, Muhammad Imran Sharif¹, Muhammad Attique Khan², Nisar Ali², Abdullah Alqahtani³, Majed Alhaisoni⁴, Ye Jin Kim⁵, Byoungchol Chang^6,*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2383-2396, 2023, DOI:10.32604/cmc.2023.033894
Abstract The content-centric networking (CCN) architecture allows access to the content through name, instead of the physical location where the content is stored, which makes it a more robust and flexible content-based architecture. Nevertheless, in CCN, the broadcast nature of vehicles on the Internet of Vehicles (IoV) results in latency and network congestion. The IoV-based content distribution is an emerging concept in which all the vehicles are connected via the internet. Due to the high mobility of vehicles, however, IoV applications have different network requirements that differ from those of many other networks, posing new challenges. Considering this, a novel strategy… More >

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454

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ARTICLE

Mohammed Mubarak Mustafa¹, Ahmed Abelmonem Khalifa^2,3, Korhan Cengiz^4,5, Nikola Ivković^6,*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2397-2412, 2023, DOI:10.32604/cmc.2023.036275
Abstract The performance of Wireless Sensor Networks (WSNs) is an important fragment of the Internet of Things (IoT), where the current WSNbuilt IoT network’s sensor hubs are enticing due to their critical resources. By grouping hubs, a clustering convention offers a useful solution for ensuring energy-saving of hubs and Hybrid Media Access Control (HMAC) during the course of the organization. Nevertheless, current grouping standards suffer from issues with the grouping structure that impacts the exhibition of these conventions negatively. In this investigation, we recommend an Improved Energy-Proficient Algorithm (IEPA) for HMAC throughout the lifetime of the WSN-based IoT. Three consecutive segments… More >

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636

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ARTICLE

Salah-ud-din Khokhar^1,2,*, QinKe Peng¹, Muhammad Yasir Noor³
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2413-2427, 2023, DOI:10.32604/cmc.2023.036148
Abstract For fuzzy systems to be implemented effectively, the fuzzy membership function (MF) is essential. A fuzzy system (FS) that implements precise input and output MFs is presented to enhance the performance and accuracy of single-input single-output (SISO) FSs and introduce the most applicable input and output MFs protocol to linearize the fuzzy system’s output. Utilizing a variety of non-linear techniques, a SISO FS is simulated. The results of FS experiments conducted in comparable conditions are then compared. The simulated results and the results of the experimental setup agree fairly well. The findings of the suggested model demonstrate that the relative… More >

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ARTICLE

Yang Zhang¹, Chaoyang Li^2,*, Xiangjun Xin²
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2429-2442, 2023, DOI:10.32604/cmc.2023.037139
Abstract Cold-chain logistics system (CCLS) plays the role of collecting and managing the logistics data of frozen food. However, there always exist problems of information loss, data tampering, and privacy leakage in traditional centralized systems, which influence frozen food security and people’s health. The centralized management form impedes the development of the cold-chain logistics industry and weakens logistics data availability. This paper first introduces a distributed CCLS based on blockchain technology to solve the centralized management problem. This system aggregates the production base, storage, transport, detection, processing, and consumer to form a cold-chain logistics union. The blockchain ledger guarantees that the… More >

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1043

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523

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ARTICLE

Zixiong Wang, Qiuying Chen, Sang-Joon Lee^*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2443-2459, 2023, DOI:10.32604/cmc.2023.037553
Abstract The rapid expansion of the non-fungible token (NFT) market has attracted many investors. However, studies on the NFT price fluctuations have been relatively limited. To date, the machine learning approach has not been used to demonstrate a specific error in NFT sale price fluctuation prediction. The aim of this study was to develop a prediction model for NFT price fluctuations using the NFT trading information obtained from OpenSea, the world’s largest NFT marketplace. We used Python programs to collect data and summarized them as: NFT information, collection information, and related account information. AdaBoost and Random Forest (RF) algorithms were employed… More >

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539

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ARTICLE

Tarique Rafique Memon^1,2,*, Tayab Din Memon^3,4, Imtiaz Hussain Kalwar⁵, Bhawani Shankar Chowdhry¹
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2461-2477, 2023, DOI:10.32604/cmc.2023.035413
Abstract Derailment of trains is not unusual all around the world, especially in developing countries, due to unidentified track or rolling stock faults that cause massive casualties each year. For this purpose, a proper condition monitoring system is essential to avoid accidents and heavy losses. Generally, the detection and classification of railway track surface faults in real-time requires massive computational processing and memory resources and is prone to a noisy environment. Therefore, in this paper, we present the development of a novel embedded system prototype for condition monitoring of railway track. The proposed prototype system works in real-time by acquiring railway… More >

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479

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ARTICLE

Fahad Mazaed Alotaibi^*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2479-2490, 2023, DOI:10.32604/cmc.2023.033792
Abstract With the progress of advanced technology in the industrial revolution encompassing the Internet of Things (IoT) and cloud computing, cyberattacks have been increasing rapidly on a large scale. The rapid expansion of IoT and networks in many forms generates massive volumes of data, which are vulnerable to security risks. As a result, cyberattacks have become a prevalent and danger to society, including its infrastructures, economy, and citizens’ privacy, and pose a national security risk worldwide. Therefore, cyber security has become an increasingly important issue across all levels and sectors. Continuous progress is being made in developing more sophisticated and efficient… More >

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840

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424

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ARTICLE

Ashir Javeed^1,2, Ana Luiza Dallora², Johan Sanmartin Berglund^2,*, Arif Ali⁴, Peter Anderberg^2,3, Liaqat Ali⁵
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2491-2508, 2023, DOI:10.32604/cmc.2023.033783
Abstract Dementia is a disorder with high societal impact and severe consequences for its patients who suffer from a progressive cognitive decline that leads to increased morbidity, mortality, and disabilities. Since there is a consensus that dementia is a multifactorial disorder, which portrays changes in the brain of the affected individual as early as 15 years before its onset, prediction models that aim at its early detection and risk identification should consider these characteristics. This study aims at presenting a novel method for ten years prediction of dementia using on multifactorial data, which comprised 75 variables. There are two automated diagnostic… More >

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ARTICLE

Shu-Yin Chiang^*, Dong-Ye Wu
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2509-2526, 2023, DOI:10.32604/cmc.2023.036466
Abstract Physiological signals indicate a person’s physical and mental state at any given time. Accordingly, many studies extract physiological signals from the human body with non-contact methods, and most of them require facial feature points. However, under COVID-19, wearing a mask has become a must in many places, so how non-contact physiological information measurements can still be performed correctly even when a mask covers the facial information has become a focus of research. In this study, RGB and thermal infrared cameras were used to execute non-contact physiological information measurement systems for heart rate, blood pressure, respiratory rate, and forehead temperature for… More >

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658

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390

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ARTICLE

Ming Cheng¹, Shiming Li^1,3,*, Yuhe Wang¹, Guohui Zhou¹, Peng Han¹, Yan Zhao²
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2527-2555, 2023, DOI:10.32604/cmc.2023.036427
Abstract To address the problem of network security situation assessment in the Industrial Internet, this paper adopts the evidential reasoning (ER)algorithm and belief rule base (BRB) method to establish an assessment model. First, this paper analyzes the influencing factors of the Industrial Internet and selects evaluation indicators that contain not only quantitative data but also qualitative knowledge. Second, the evaluation indicators are fused with expert knowledge and the ER algorithm. According to the fusion results, a network security situation assessment model of the Industrial Internet based on the ER and BRB method is established, and the projection covariance matrix adaptive evolution… More >

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437

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3

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ARTICLE

Karim Gasmi^1,*, Lassaad Ben Ammar^2,, Hmoud Elshammari⁴, Fadwa Yahya²
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2557-2573, 2023, DOI:10.32604/cmc.2023.033270
Abstract Convolution neural networks (CNNs) have proven to be effective clinical imaging methods. This study highlighted some of the key issues within these systems. It is difficult to train these systems in a limited clinical image databases, and many publications present strategies including such learning algorithm. Furthermore, these patterns are known for making a highly reliable prognosis. In addition, normalization of volume and losses of dice have been used effectively to accelerate and stabilize the training. Furthermore, these systems are improperly regulated, resulting in more confident ratings for correct and incorrect classification, which are inaccurate and difficult to understand. This study… More >

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400

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ARTICLE

Badriyya B. Al-onazi¹, Abdulkhaleq Q. A. Hassan², Mohamed K. Nour³, Mesfer Al Duhayyim^4,*, Abdullah Mohamed⁵, Amgad Atta Abdelmageed⁶, Ishfaq Yaseen⁶, Gouse Pasha Mohammed⁶
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2575-2591, 2023, DOI:10.32604/cmc.2023.033531
Abstract Sentiment Analysis (SA), a Machine Learning (ML) technique, is often applied in the literature. The SA technique is specifically applied to the data collected from social media sites. The research studies conducted earlier upon the SA of the tweets were mostly aimed at automating the feature extraction process. In this background, the current study introduces a novel method called Quantum Particle Swarm Optimization with Deep Learning-Based Sentiment Analysis on Arabic Tweets (QPSODL-SAAT). The presented QPSODL-SAAT model determines and classifies the sentiments of the tweets written in Arabic. Initially, the data pre-processing is performed to convert the raw tweets into a… More >

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753

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586

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ARTICLE

Tayyaba Noreen^1,*, Qiufen Xia¹, Muhammad Zeeshan Haider²
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2593-2613, 2023, DOI:10.32604/cmc.2023.036139
Abstract In the past decade, blockchain has evolved as a promising solution to develop secure distributed ledgers and has gained massive attention. However, current blockchain systems face the problems of limited throughput, poor scalability, and high latency. Due to the failure of consensus algorithms in managing nodes’identities, blockchain technology is considered inappropriate for many applications, e.g., in IoT environments, because of poor scalability. This paper proposes a blockchain consensus mechanism called the Advanced DAG-based Ranking (ADR) protocol to improve blockchain scalability and throughput. The ADR protocol uses the directed acyclic graph ledger, where nodes are placed according to their ranking positions… More >

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1085

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523

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ARTICLE

Navin Ranjan¹, Sovit Bhandari¹, Yeong-Chan Kim^1,2, Hoon Kim^1,2,*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2615-2639, 2023, DOI:10.32604/cmc.2023.026086
Abstract Video prediction is the problem of generating future frames by exploiting the spatiotemporal correlation from the past frame sequence. It is one of the crucial issues in computer vision and has many real-world applications, mainly focused on predicting future scenarios to avoid undesirable outcomes. However, modeling future image content and object is challenging due to the dynamic evolution and complexity of the scene, such as occlusions, camera movements, delay and illumination. Direct frame synthesis or optical-flow estimation are common approaches used by researchers. However, researchers mainly focused on video prediction using one of the approaches. Both methods have limitations, such… More >

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846

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423

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ARTICLE

Ghofran Kh. Shraida¹, Hameed A. Younis¹, Taief Alaa Al-Amiedy², Mohammed Anbar^2,*, Hussain A. Younis^3,4, Iznan H. Hasbullah²
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2641-2654, 2023, DOI:10.32604/cmc.2023.035793
Abstract Nowadays, high-resolution images pose several challenges in the context of image encryption. The encryption of huge images’ file sizes requires high computational resources. Traditional encryption techniques like, Data Encryption Standard (DES), and Advanced Encryption Standard (AES) are not only inefficient, but also less secure. Due to characteristics of chaos theory, such as periodicity, sensitivity to initial conditions and control parameters, and unpredictability. Hence, the characteristics of deoxyribonucleic acid (DNA), such as vast parallelism and large storage capacity, make it a promising field. This paper presents an efficient color image encryption method utilizing DNA encoding with two types of hyper-chaotic maps.… More >

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965

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708

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ARTICLE

Ling Ding¹, Hongyan Wan^2,*, Luokai Hu¹, Yu Chen¹
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2655-2670, 2023, DOI:10.32604/cmc.2023.035542
Abstract Product detection based on state abstraction technologies in the software product line (SPL) is more complex when compared to a single system. This variability constitutes a new complexity, and the counterexample may be valid for some products but spurious for others. In this paper, we found that spurious products are primarily due to the failure states, which correspond to the spurious counterexamples. The violated products correspond to the real counterexamples. Hence, identifying counterexamples is a critical problem in detecting violated products. In our approach, we obtain the violated products through the genuine counterexamples, which have no failure state, to avoid… More >

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632

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378

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ARTICLE

Liwei Deng¹, Yuanzhi Zhang¹, Xin Yang^2,*, Sijuan Huang², Jing Wang^3,*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2671-2684, 2023, DOI:10.32604/cmc.2023.036642
Abstract High-resolution medical images have important medical value, but are difficult to obtain directly. Limited by hardware equipment and patient’s physical condition, the resolution of directly acquired medical images is often not high. Therefore, many researchers have thought of using super-resolution algorithms for secondary processing to obtain high-resolution medical images. However, current super-resolution algorithms only work on a single scale, and multiple networks need to be trained when super-resolution images of different scales are needed. This definitely raises the cost of acquiring high-resolution medical images. Thus, we propose a multi-scale super-resolution algorithm using meta-learning. The algorithm combines a meta-learning approach with… More >

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450

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ARTICLE

Khaled M. Suwais^*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2685-2704, 2023, DOI:10.32604/cmc.2023.036161
Abstract Data encryption is essential in securing exchanged data between connected parties. Encryption is the process of transforming readable text into scrambled, unreadable text using secure keys. Stream ciphers are one type of an encryption algorithm that relies on only one key for decryption and as well as encryption. Many existing encryption algorithms are developed based on either a mathematical foundation or on other biological, social or physical behaviours. One technique is to utilise the behavioural aspects of game theory in a stream cipher. In this paper, we introduce an enhanced Deoxyribonucleic acid (DNA)-coded stream cipher based on an iterated n-player… More >

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505

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382

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ARTICLE

Sangyun Lee¹, Junekoo Kang², Hyunki Hong^2,*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2705-2725, 2023, DOI:10.32604/cmc.2023.034136
Abstract In feature-based visual localization for small-scale scenes, local descriptors are used to estimate the camera pose of a query image. For large and ambiguous environments, learning-based hierarchical networks that employ local as well as global descriptors to reduce the search space of database images into a smaller set of reference views have been introduced. However, since global descriptors are generated using visual features, reference images with some of these features may be erroneously selected. In order to address this limitation, this paper proposes two clustering methods based on how often features appear as well as their covisibility. For both approaches,… More >

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ARTICLE

Maryam Alhassan, Abdul Raouf Khan^*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2727-2740, 2023, DOI:10.32604/cmc.2023.037129
Abstract Preserving privacy is imperative in the new unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) architecture to ensure that sensitive information is protected and kept secure throughout the communication. Simultaneously, efficiency must be considered while developing such a privacy-preserving scheme because the devices involved in these architectures are resource constrained. This study proposes a lightweight and efficient authentication scheme for the UAV-assisted MEC environment. The proposed scheme is a hardware-based password-less authentication mechanism that is based on the fact that temporal and memory-related efficiency can be significantly improved while maintaining the data security by adopting a hardware-based solution with a… More >

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2

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ARTICLE

Muhammad Usman Sana^1,*, Zhanli Li¹, Tayybah Kiren², Hannan Bin Liaqat³, Shahid Naseem³, Atif Saeed⁴
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2741-2757, 2023, DOI:10.32604/cmc.2023.036093
Abstract Cloud computing is a technology that provides secure storage space for the customer’s massive data and gives them the facility to retrieve and transmit their data efficiently through a secure network in which encryption and decryption algorithms are being deployed. In cloud computation, data processing, storage, and transmission can be done through laptops and mobile devices. Data Storing in cloud facilities is expanding each day and data is the most significant asset of clients. The important concern with the transmission of information to the cloud is security because there is no perceivability of the client’s data. They have to be… More >

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518

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ARTICLE

Tiansu Chen^1,2, Shi bin Zhang^1,2, Qirun Wang³, Yan Chang^1,2,*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2759-2773, 2023, DOI:10.32604/cmc.2023.033284
Abstract In the era of big data, traditional regression models cannot deal with uncertain big data efficiently and accurately. In order to make up for this deficiency, this paper proposes a quantum fuzzy regression model, which uses fuzzy theory to describe the uncertainty in big data sets and uses quantum computing to exponentially improve the efficiency of data set preprocessing and parameter estimation. In this paper, data envelopment analysis (DEA) is used to calculate the degree of importance of each data point. Meanwhile, Harrow, Hassidim and Lloyd (HHL) algorithm and quantum swap circuits are used to improve the efficiency of high-dimensional… More >

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605

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415

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ARTICLE

Dongyang Li¹, Shiyu Du^2,*, Yiming Zhang², Meiting Zhao³
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2775-2803, 2023, DOI:10.32604/cmc.2023.035911
Abstract Metaheuristic algorithms, as effective methods for solving optimization problems, have recently attracted considerable attention in science and engineering fields. They are popular and have broad applications owing to their high efficiency and low complexity. These algorithms are generally based on the behaviors observed in nature, physical sciences, or humans. This study proposes a novel metaheuristic algorithm called dark forest algorithm (DFA), which can yield improved optimization results for global optimization problems. In DFA, the population is divided into four groups: highest civilization, advanced civilization, normal civilization, and low civilization. Each civilization has a unique way of iteration. To verify DFA’s… More >

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2

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ARTICLE

Emad Sami Jaha^*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2805-2831, 2023, DOI:10.32604/cmc.2023.036169
Abstract A document layout can be more informative than merely a document’s visual and structural appearance. Thus, document layout analysis (DLA) is considered a necessary prerequisite for advanced processing and detailed document image analysis to be further used in several applications and different objectives. This research extends the traditional approaches of DLA and introduces the concept of semantic document layout analysis (SDLA) by proposing a novel framework for semantic layout analysis and characterization of handwritten manuscripts. The proposed SDLA approach enables the derivation of implicit information and semantic characteristics, which can be effectively utilized in dozens of practical applications for various… More >

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REVIEW

Norah M. Alshahrani^1,2,*, M. L. Mat Kiah^1,*, B. B. Zaidan³, A. H. Alamoodi⁴, Abdu Saif⁵
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2833-2858, 2023, DOI:10.32604/cmc.2023.036138
Abstract A smart contract is a digital program of transaction protocol (rules of contract) based on the consensus architecture of blockchain. Smart contracts with Blockchain are modern technologies that have gained enormous attention in scientific and practical applications. A smart contract is the central aspect of a blockchain that facilitates blockchain as a platform outside the cryptocurrency spectrum. The development of blockchain technology, with a focus on smart contracts, has advanced significantly in recent years. However, research on the smart contract idea has weaknesses in the implementation sectors based on a decentralized network that shares an identical state. This paper extensively… More >

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ARTICLE

Muhammad Aadil Siddiqui^1,*, M. H. Md Khir¹, Zaka Ullah², Muath Al Hasan², Abdul Saboor³, Saeed Ahmed Magsi¹
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2859-2871, 2023, DOI:10.32604/cmc.2023.034164
Abstract One of the most pressing concerns for the consumer market is the detection of adulteration in meat products due to their preciousness. The rapid and accurate identification mechanism for lard adulteration in meat products is highly necessary, for developing a mechanism trusted by consumers and that can be used to make a definitive diagnosis. Fourier Transform Infrared Spectroscopy (FTIR) is used in this work to identify lard adulteration in cow, lamb, and chicken samples. A simplified extraction method was implied to obtain the lipids from pure and adulterated meat. Adulterated samples were obtained by mixing lard with chicken, lamb, and… More >

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626

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427

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ARTICLE

Zhaoliang Wu¹, Shanyu Tang², Xiaoli Feng¹, Jiajun Zou³, Fulian Yin^1,4,*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2873-2888, 2023, DOI:10.32604/cmc.2023.037060
Abstract Aspect-Based Sentiment Analysis (ABSA) is one of the essential research in the field of Natural Language Processing (NLP), of which Aspect Sentiment Quad Prediction (ASQP) is a novel and complete subtask. ASQP aims to accurately recognize the sentiment quad in the target sentence, which includes the aspect term, the aspect category, the corresponding opinion term, and the sentiment polarity of opinion. Nevertheless, existing approaches lack knowledge of the sentence’s syntax, so despite recent innovations in ASQP, it is poor for complex cyber comment processing. Also, most research has focused on processing English text, and ASQP for Chinese text is almost… More >

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594

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427

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ARTICLE

Zhao Yang¹, Yuan Zhang¹, Lei Zhu^2,*, Lei Huang¹, Fangyu Hu³, Yanping Du¹, Xiaowei Li¹
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2889-2904, 2023, DOI:10.32604/cmc.2023.037297
Abstract High-frequency (HF) and ultrahigh-frequency (UHF) dual-band radio frequency identification (RFID) tags with both near-field and far-field communication can meet different application scenarios. However, it is time-consuming to calculate the return loss of a UHF antenna in a dual-band tag antenna using electromagnetic (EM) simulators. To overcome this, the present work proposes a model of a multi-scale convolutional neural network stacked with long and short-term memory (MSCNN-LSTM) for predicting the return loss of UHF antennas instead of EM simulators. In the proposed MSCNN-LSTM, the MSCNN has three branches, which include three convolution layers with different kernel sizes and numbers. Therefore, MSCNN… More >

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794

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485

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ARTICLE

Raed Saeed Rasheed¹, Khalil Hamdi Ateyeh Al-Shqeerat^2,*, Ahmed Salah Ghorab³, Fuad Salama AbuOwaimer⁴, Aiman Ahmed AbuSamra¹
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2905-2919, 2023, DOI:10.32604/cmc.2023.036691
Abstract There has been an increase in the adoption of mobile payment systems worldwide in the past few years. However, poor Internet connection in rural regions continues to be an obstacle to the widespread use of such technologies. On top of that, there are significant problems with the currently available offline wallets; for instance, the payee cannot verify the number of coins received without access to the Internet. Additionally, it has been demonstrated that some existing systems are susceptible to false token generation, and some do not even permit the user to divide the offline token into smaller portions to be… More >

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790

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530

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ARTICLE

Muhammad Asfand-e-Yar^1,*, Qadeer Hashir^1,*, Syed Hassan Tanvir¹, Wajeeha Khalil²
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2921-2938, 2023, DOI:10.32604/cmc.2023.034741
Abstract The growth of the internet and technology has had a significant effect on social interactions. False information has become an important research topic due to the massive amount of misinformed content on social networks. It is very easy for any user to spread misinformation through the media. Therefore, misinformation is a problem for professionals, organizers, and societies. Hence, it is essential to observe the credibility and validity of the News articles being shared on social media. The core challenge is to distinguish the difference between accurate and false information. Recent studies focus on News article content, such as News titles… More >

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553

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ARTICLE

Zerui Zhen¹, Zihao Wu², Lei Feng^1,*, Wenjing Li¹, Feng Qi¹, Shixuan Guo¹
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2939-2955, 2023, DOI:10.32604/cmc.2023.036505
Abstract Asynchronous federated learning (AsynFL) can effectively mitigate the impact of heterogeneity of edge nodes on joint training while satisfying participant user privacy protection and data security. However, the frequent exchange of massive data can lead to excess communication overhead between edge and central nodes regardless of whether the federated learning (FL) algorithm uses synchronous or asynchronous aggregation. Therefore, there is an urgent need for a method that can simultaneously take into account device heterogeneity and edge node energy consumption reduction. This paper proposes a novel Fixed-point Asynchronous Federated Learning (FixedAsynFL) algorithm, which could mitigate the resource consumption caused by frequent… More >

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ARTICLE

Zibo Wang^1,3, Chaobin Huo², Yaofang Zhang^1,3, Shengtao Cheng^1,3, Yilu Chen^1,3, Xiaojie Wei⁵, Chao Li⁴, Bailing Wang^1,3,*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2957-2979, 2023, DOI:10.32604/cmc.2023.035694
Abstract With the growing discovery of exposed vulnerabilities in the Industrial Control Components (ICCs), identification of the exploitable ones is urgent for Industrial Control System (ICS) administrators to proactively forecast potential threats. However, it is not a trivial task due to the complexity of the multi-source heterogeneous data and the lack of automatic analysis methods. To address these challenges, we propose an exploitability reasoning method based on the ICC-Vulnerability Knowledge Graph (KG) in which relation paths contain abundant potential evidence to support the reasoning. The reasoning task in this work refers to determining whether a specific relation is valid between an… More >

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371

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ARTICLE

Huma Israr^1,*, Safdar Abbas Khan¹, Muhammad Ali Tahir¹, Muhammad Khuram Shahzad¹, Muneer Ahmad¹, Jasni Mohamad Zain^2,*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2981-3009, 2023, DOI:10.32604/cmc.2023.035814
Abstract In bilingual translation, attention-based Neural Machine Translation (NMT) models are used to achieve synchrony between input and output sequences and the notion of alignment. NMT model has obtained state-of-the-art performance for several language pairs. However, there has been little work exploring useful architectures for Urdu-to-English machine translation. We conducted extensive Urdu-to-English translation experiments using Long short-term memory (LSTM)/Bidirectional recurrent neural networks (Bi-RNN)/Statistical recurrent unit (SRU)/Gated recurrent unit (GRU)/Convolutional neural network (CNN) and Transformer. Experimental results show that Bi-RNN and LSTM with attention mechanism trained iteratively, with a scalable data set, make precise predictions on unseen data. The trained models yielded… More >

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Amjad Hussain Zahid¹, Muhammad Junaid Arshad², Musheer Ahmad^3,*, Naglaa F. Soliman⁴, Walid El-Shafai^5,6
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3011-3026, 2023, DOI:10.32604/cmc.2023.037516
Abstract A substitution box (S-Box) is a crucial component of contemporary cryptosystems that provide data protection in block ciphers. At the moment, chaotic maps are being created and extensively used to generate these S-Boxes as a chaotic map assists in providing disorder and resistance to combat cryptanalytical attempts. In this paper, the construction of a dynamic S-Box using a cipher key is proposed using a novel chaotic map and an innovative tweaking approach. The projected chaotic map and the proposed tweak approach are presented for the first time and the use of parameters in their working makes both of these dynamic… More >

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Youngmin Kim¹, Sunwoo Hwang², Jaemin Park¹, Joouk Kim^2,*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3027-3044, 2023, DOI:10.32604/cmc.2023.027877
Abstract With the growth of the online market, demand for logistics and courier cargo is increasing rapidly. Accordingly, in the case of urban areas, road congestion and environmental problems due to cargo vehicles are mainly occurring. The joint courier logistics system, a plan to solve this problem, aims to establish an efficient logistics transportation system by utilizing one joint logistics delivery terminal by several logistics and delivery companies. However, several courier companies use different types of courier invoices. Such a system has a problem of information data transmission interruption. Therefore, the data processing process was systematically analyzed, a practically feasible methodology… More >

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Omar Abdulghafoor¹, Musbah Shaat², Ibraheem Shayea³, Ahmad Hamood¹, Abdelzahir Abdelmaboud⁴, Ashraf Osman Ibrahim⁵, Fadhil Mukhlif^6,*, Herish Badal¹, Norafida Ithnin⁶, Ali Khadim Lwas⁷
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3045-3064, 2023, DOI:10.32604/cmc.2023.033888
Abstract The computational complexity of resource allocation processes, in cognitive radio networks (CRNs), is a major issue to be managed. Furthermore, the complicated solution of the optimal algorithm for handling resource allocation in CRNs makes it unsuitable to adopt in real-world applications where both cognitive users, CRs, and primary users, PUs, exist in the identical geographical area. Hence, this work offers a primarily price-based power algorithm to reduce computational complexity in uplink scenarios while limiting interference to PUs to allowable threshold. Hence, this paper, compared to other frameworks proposed in the literature, proposes a two-step approach to reduce the complexity of… More >

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Ali Arshad^1,*, Muhammad Nadeem², Saman Riaz¹, Syeda Wajiha Zahra², Ashit Kumar Dutta³, Zaid Alzaid⁴, Rana Alabdan⁵, Badr Almutairi⁶, Sultan Almotairi^4,7
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3065-3089, 2023, DOI:10.32604/cmc.2023.035695
Abstract There are many cloud data security techniques and algorithms available that can be used to detect attacks on cloud data, but these techniques and algorithms cannot be used to protect data from an attacker. Cloud cryptography is the best way to transmit data in a secure and reliable format. Various researchers have developed various mechanisms to transfer data securely, which can convert data from readable to unreadable, but these algorithms are not sufficient to provide complete data security. Each algorithm has some data security issues. If some effective data protection techniques are used, the attacker will not be able to… More >

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Eric Yocam¹, Ahmad Alomari², Amjad Gawanmeh^3,*, Wathiq Mansoor³
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3091-3110, 2023, DOI:10.32604/cmc.2023.032826
Abstract A person’s privacy has become a growing concern, given the nature of an expansive reliance on real-time video activities with video capture, stream, and storage. This paper presents an innovative system design based on a privacy-preserving model. The proposed system design is implemented by employing an enhanced capability that overcomes today’s single parameter-based access control protection mechanism for digital privacy preservation. The enhanced capability combines multiple access control parameters: facial expression, resource, environment, location, and time. The proposed system design demonstrated that a person’s facial expressions combined with a set of access control rules can achieve a person’s privacy-preserving preferences.… More >

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Wenlong Zhu^1,*, Yu Miao¹, Shuangshuang Yang², Zuozheng Lian¹, Lianhe Cui¹
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3111-3131, 2023, DOI:10.32604/cmc.2023.036159
Abstract Influence maximization of temporal social networks (IMT) is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely spread. To solve the IMT problem, we propose an influence maximization algorithm based on an improved K-shell method, namely improved K-shell in temporal social networks (KT). The algorithm takes into account the global and local structures of temporal social networks. First, to obtain the kernel value Ks of each node, in the global scope, it layers the network according to the temporal characteristic of nodes by improving… More >

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Osama A. Khashan^1,*, Sultan Alamri², Waleed Alomoush³, Mutasem K. Alsmadi⁴, Samer Atawneh², Usama Mir⁵
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3133-3158, 2023, DOI:10.32604/cmc.2023.036217
Abstract In recent times, technology has advanced significantly and is currently being integrated into educational environments to facilitate distance learning and interaction between learners. Integrating the Internet of Things (IoT) into education can facilitate the teaching and learning process and expand the context in which students learn. Nevertheless, learning data is very sensitive and must be protected when transmitted over the network or stored in data centers. Moreover, the identity and the authenticity of interacting students, instructors, and staff need to be verified to mitigate the impact of attacks. However, most of the current security and authentication schemes are centralized, relying… More >

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Tzu-Chia Chen¹, Ngakan Ketut Acwin Dwijendra^2,*, Saurabh Singhal³, R. Sivaraman⁴, Amr Mamdouh⁵
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3159-3169, 2023, DOI:10.32604/cmc.2023.035418
Abstract A smart city incorporates infrastructure methods that are environmentally responsible, such as smart communications, smart grids, smart energy, and smart buildings. The city administration has prioritized the use of cutting-edge technology and informatics as the primary strategy for enhancing service quality, with energy resources taking precedence. To achieve optimal energy management in the multidimensional system of a city tribe, it is necessary not only to identify and study the vast majority of energy elements, but also to define their implicit interdependencies. This is because optimal energy management is required to reach this objective. The lighting index is an essential consideration… More >

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Chandana Gouri Tekkali, Karthika Natarajan^*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3171-3187, 2023, DOI:10.32604/cmc.2023.036865
Abstract Fraud Transactions are haunting the economy of many individuals with several factors across the globe. This research focuses on developing a mechanism by integrating various optimized machine-learning algorithms to ensure the security and integrity of digital transactions. This research proposes a novel methodology through three stages. Firstly, Synthetic Minority Oversampling Technique (SMOTE) is applied to get balanced data. Secondly, SMOTE is fed to the nature-inspired Meta Heuristic (MH) algorithm, namely Binary Harris Hawks Optimization (BinHHO), Binary Aquila Optimization (BAO), and Binary Grey Wolf Optimization (BGWO), for feature selection. BinHHO has performed well when compared with the other two. Thirdly, features… More >

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Shakti Raj Chopra¹, Parulpreet Singh¹, Ahmed Alhussen^2,*, Nitin Mittal³, MohdAnul Haq⁴
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3189-3201, 2023, DOI:10.32604/cmc.2023.030061
Abstract Many extensive UAV communication networks have used UAV cooperative control. Wireless networking services can be offered using unmanned aerial vehicles (UAVs) as aerial base stations. Not only is coverage maximization, but also better connectivity, a fundamental design challenge that must be solved. The number of applications for unmanned aerial vehicles (UAVs) operating in unlicensed bands is fast expanding as the Internet of Things (IoT) develops. Those bands, however, have become overcrowded as the number of systems that use them grows. Cognitive Radio (CR) and spectrum allocation approaches have emerged as a potential approach for resolving spectrum scarcity in wireless networks,… More >

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Chuan-Yang Ruan^1,2, Xiang-Jing Chen¹, Li-Na Han^3,*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3203-3222, 2023, DOI:10.32604/cmc.2023.035480
Abstract In real life, incomplete information, inaccurate data, and the preferences of decision-makers during qualitative judgment would impact the process of decision-making. As a technical instrument that can successfully handle uncertain information, Fermatean fuzzy sets have recently been used to solve the multi-attribute decision-making (MADM) problems. This paper proposes a Fermatean hesitant fuzzy information aggregation method to address the problem of fusion where the membership, non-membership, and priority are considered simultaneously. Combining the Fermatean hesitant fuzzy sets with Heronian Mean operators, this paper proposes the Fermatean hesitant fuzzy Heronian mean (FHFHM) operator and the Fermatean hesitant fuzzy weighted Heronian mean (FHFWHM)… More >

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Alawi Alqushaibi^1,2,*, Mohd Hilmi Hasan^1,2, Said Jadid Abdulkadir^1,2, Amgad Muneer^1,2, Mohammed Gamal^1,2, Qasem Al-Tashi³, Shakirah Mohd Taib^1,2, Hitham Alhussian^1,2
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3223-3238, 2023, DOI:10.32604/cmc.2023.035655
Abstract Diabetes mellitus is a long-term condition characterized by hyperglycemia. It could lead to plenty of difficulties. According to rising morbidity in recent years, the world’s diabetic patients will exceed 642 million by 2040, implying that one out of every ten persons will be diabetic. There is no doubt that this startling figure requires immediate attention from industry and academia to promote innovation and growth in diabetes risk prediction to save individuals’ lives. Due to its rapid development, deep learning (DL) was used to predict numerous diseases. However, DL methods still suffer from their limited prediction performance due to the hyperparameters… More >

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Majdy M. Eltahir¹, Adil Yousif², Fadwa Alrowais³, Mohamed K. Nour⁴, Radwa Marzouk⁵, Hatim Dafaalla⁶, Asma Abbas Hassan Elnour⁶, Amira Sayed A. Aziz⁷, Manar Ahmed Hamza^8,*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3239-3255, 2023, DOI:10.32604/cmc.2023.034037
Abstract The human motion data collected using wearables like smartwatches can be used for activity recognition and emergency event detection. This is especially applicable in the case of elderly or disabled people who live self-reliantly in their homes. These sensors produce a huge volume of physical activity data that necessitates real-time recognition, especially during emergencies. Falling is one of the most important problems confronted by older people and people with movement disabilities. Numerous previous techniques were introduced and a few used webcam to monitor the activity of elderly or disabled people. But, the costs incurred upon installation and operation are high,… More >

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Kyungmin Sim, Jeong Hyun Yi, Haehyun Cho^*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3257-3274, 2023, DOI:10.32604/cmc.2023.036695
Abstract Despite the advances in automated vulnerability detection approaches, security vulnerabilities caused by design flaws in software systems are continuously appearing in real-world systems. Such security design flaws can bring unrestricted and misimplemented behaviors of a system and can lead to fatal vulnerabilities such as remote code execution or sensitive data leakage. Therefore, it is an essential task to discover unrestricted and misimplemented behaviors of a system. However, it is a daunting task for security experts to discover such vulnerabilities in advance because it is time-consuming and error-prone to analyze the whole code in detail. Also, most of the existing vulnerability… More >

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Ali Raza¹, Samia Allaoua Chelloug^2,*, Mohammed Hamad Alatiyyah³, Ahmad Jalal¹, Jeongmin Park⁴
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3275-3289, 2023, DOI:10.32604/cmc.2023.029719
Abstract Pedestrian detection and tracking are vital elements of today’s surveillance systems, which make daily life safe for humans. Thus, human detection and visualization have become essential inventions in the field of computer vision. Hence, developing a surveillance system with multiple object recognition and tracking, especially in low light and night-time, is still challenging. Therefore, we propose a novel system based on machine learning and image processing to provide an efficient surveillance system for pedestrian detection and tracking at night. In particular, we propose a system that tackles a two-fold problem by detecting multiple pedestrians in infrared (IR) images using machine… More >

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