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  • Open Access

    ARTICLE

    Cost and Efficiency Analysis of Steganography in the IEEE 802.11ah IoT Protocol

    Akram A. Almohammedi1,2,*, Vladimir Shepelev1, Sam Darshi3, Mohammed Balfaqih4, Fayad Ghawbar5

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3929-3943, 2022, DOI:10.32604/cmc.2022.026307

    Abstract The widespread use of the Internet of Things (IoT) applications has enormously increased the danger level of data leakage and theft in IoT as data transmission occurs through a public channel. As a result, the security of the IoT has become a serious challenge in the field of information security. Steganography on the network is a critical tool for preventing the leakage of private information and enabling secure and encrypted communication. The primary purpose of steganography is to conceal sensitive information in any form of media such as audio, video, text, or photos, and securely transfer it through wireless networks.… More >

  • Open Access

    ARTICLE

    Fuzzy Aggregator Based Energy Aware RPL Routing for IoT Enabled Forest Environment

    S. Srividhya1, Suresh Sankaranarayanan2,*, Sergei A. Kozlov3, Joel J. P. C. Rodrigues3,4,5

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 4039-4055, 2022, DOI:10.32604/cmc.2022.026306

    Abstract Forested areas are extremely vulnerable to disasters leading to environmental destruction. Forest Fire is one among them which requires immediate attention. There are lot of works done by authors where Wireless Sensors and IoT have been used for forest fire monitoring. So, towards monitoring the forest fire and managing the energy efficiently in IoT, Energy Efficient Routing Protocol for Low power lossy networks (E-RPL) was developed. There were challenges about the scalability of the network resulting in a large end-to-end delay and less packet delivery which led to the development of Aggregator-based Energy Efficient RPL with Data Compression (CAA-ERPL). Though… More >

  • Open Access

    ARTICLE

    Two-Stage PLS-SEM and Fuzzy AHP Approach to Investigate Vietnamese SMEs’ Export Competitiveness

    Phi-Hung Nguyen1,2,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 4107-4123, 2022, DOI:10.32604/cmc.2022.026286

    Abstract Vietnam is paying great to the seafood exporting sector, offering various significant production advantages, concluding that it is critical to understand the competitiveness of the target market and implement effective strategies. However, due to COVID 19, the value of Vietnamese pangasius exports resulted in low and unpredictable profits for pangasius farmers. It is obvious to recognize competitiveness as Multi-Criteria Decision Making (MCDM) problem in the uncertain business environment. Therefore, this study is the first to propose a two-staged Partial Least Squares-Structural Equation Modeling (PLS-SEM) and Fuzzy Analytic Hierarchy Process (FAHP) analysis to identify potential criteria and comprehensively investigate the competitiveness… More >

  • Open Access

    ARTICLE

    AI-based Automated Extraction of Location-Oriented COVID-19 Sentiments

    Fahim K. Sufi1,*, Musleh Alsulami2

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3631-3649, 2022, DOI:10.32604/cmc.2022.026272

    Abstract The coronavirus disease (COVID-19) pandemic has affected the lives of social media users in an unprecedented manner. They are constantly posting their satisfaction or dissatisfaction over the COVID-19 situation at their location of interest. Therefore, understanding location-oriented sentiments about this situation is of prime importance for political leaders, and strategic decision-makers. To this end, we present a new fully automated algorithm based on artificial intelligence (AI), for extraction of location-oriented public sentiments on the COVID-19 situation. We designed the proposed system to obtain exhaustive knowledge and insights on social media feeds related to COVID-19 in 110 languages through AI-based translation,… More >

  • Open Access

    ARTICLE

    Intelligent Forensic Investigation Using Optimal Stacked Autoencoder for Critical Industrial Infrastructures

    Abdullah S. AL-Malaise AL-Ghamdi1, Mahmoud Ragab2,3,4,*, F. J. Alsolami5, Hani Choudhry3,6, Ibrahim Rizqallah Alzahrani7

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2275-2289, 2022, DOI:10.32604/cmc.2022.026226

    Abstract Industrial Control Systems (ICS) can be employed on the industrial processes in order to reduce the manual labor and handle the complicated industrial system processes as well as communicate effectively. Internet of Things (IoT) integrates numerous sets of sensors and devices via a data network enabling independent processes. The incorporation of the IoT in the industrial sector leads to the design of Industrial Internet of Things (IIoT), which find use in water distribution system, power plants, etc. Since the IIoT is susceptible to different kinds of attacks due to the utilization of Internet connection, an effective forensic investigation process becomes… More >

  • Open Access

    ARTICLE

    Deep Learning Framework for Precipitation Prediction Using Cloud Images

    Mirza Adnan Baig*, Ghulam Ali Mallah, Noor Ahmed Shaikh

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 4201-4213, 2022, DOI:10.32604/cmc.2022.026225

    Abstract Precipitation prediction (PP) have become one of the significant research areas of deep learning (DL) and machine vision (MV) techniques are frequently used to predict the weather variables (WV). Since the climate change has left significant impact upon weather variables (WV) and continuously changes are observed in temperature, humidity, cloud patterns and other factors. Although cloud images contain sufficient information to predict the precipitation pattern but due to changes in climate, the complex cloud patterns and rapid shape changing behavior of clouds are difficult to consider for rainfall prediction. Prediction of rainfall would provide more meticulous assistance to the farmers… More >

  • Open Access

    ARTICLE

    Intelligent Feature Selection with Deep Learning Based Financial Risk Assessment Model

    Thavavel Vaiyapuri1, K. Priyadarshini2, A. Hemlathadhevi3, M. Dhamodaran4, Ashit Kumar Dutta5, Irina V. Pustokhina6,*, Denis A. Pustokhin7

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

    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 feature selection (WSOA-FS) manner to… More >

  • Open Access

    ARTICLE

    Embedded Coded Relay System for Molecular Communications

    Eman S. Attia1, Ashraf A. M. Khalaf1, Fathi E. Abd El-Samie2, Saied M. Abd El-atty2, Konstantinos A. Lizos3, Osama Alfarraj4, Farid Shawki2, Imran Khan5, Ki-Il Kim6,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2729-2748, 2022, DOI:10.32604/cmc.2022.026197

    Abstract With the emergence of the COVID-19 pandemic, the World Health Organization (WHO) has urged scientists and industrialists to explore modern information and communication technology (ICT) as a means to reduce or even eliminate it. The World Health Organization recently reported that the virus may infect the organism through any organ in the living body, such as the respiratory, the immunity, the nervous, the digestive, or the cardiovascular system. Targeting the abovementioned goal, we envision an implanted nanosystem embedded in the intra living-body network. The main function of the nanosystem is either to perform diagnosis and mitigation of infectious diseases or… More >

  • Open Access

    ARTICLE

    A Sparse Optimization Approach for Beyond 5G mmWave Massive MIMO Networks

    Waleed Shahjehan1, Abid Ullah1, Syed Waqar Shah1, Imran Khan1, Nor Samsiah Sani2, Ki-Il Kim3,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2797-2810, 2022, DOI:10.32604/cmc.2022.026185

    Abstract Millimeter-Wave (mmWave) Massive MIMO is one of the most effective technology for the fifth-generation (5G) wireless networks. It improves both the spectral and energy efficiency by utilizing the 30–300 GHz millimeter-wave bandwidth and a large number of antennas at the base station. However, increasing the number of antennas requires a large number of radio frequency (RF) chains which results in high power consumption. In order to reduce the RF chain's energy, cost and provide desirable quality-of-service (QoS) to the subscribers, this paper proposes an energy-efficient hybrid precoding algorithm for mmWave massive MIMO networks based on the idea of RF chains… More >

  • Open Access

    ARTICLE

    Resistance to Malicious Packet Droppers Through Enhanced AODV in a MANET

    Shirina Samreen*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 4087-4106, 2022, DOI:10.32604/cmc.2022.026141

    Abstract Packet dropping in a mobile ad hoc network can manifest itself as the data plane attacks as well as control plane attacks. The former deal with malicious nodes performing packet drop on the data packets following the route formation and the latter deal with those malicious nodes which either drop or manipulate the control packets to degrade the network performance. The idea of the proposed approach is that during the route establishment, each of the on-path nodes is provided with pre-computed hash values which have to be used to provide a unique acknowledgement value to the upstream neighbor which acts… More >

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